GSEA Class2: Canonical Pathways enriched in each subtypes of mRNAseq_cNMF in ACC-TP
Adrenocortical Carcinoma (Primary solid tumor)
02 April 2015 | analyses__2015_04_02
Maintainer Information
Citation Information
doi:10.7908/C1WD3ZHQ
Maintained by Juok Cho (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2015): GSEA Class2: Canonical Pathways enriched in each subtypes of mRNAseq_cNMF in ACC-TP. Broad Institute of MIT and Harvard. doi:10.7908/C1WD3ZHQ
Overview
Introduction

This pipeline performs Gene Set Enrichment Analysis (GSEA) using The Broad Institute GSEA tool with MSigDB - Class2: Canonical Pathways gene sets. For a given phenotype subtype, it shows what pathways are significantly enriched in each subtype by comparing gene expression profiles between subtypes. Here, the phenotype is mRNAseq_cNMF subtypes in ACC-TP. This pipeline has the following features:

1. For each subtype, calculates enrichment scores (ES) using signal to noise (S2N) that checks similarity between subtypes in expression level then calculates p values through permutation test.

2. Lists pathways significantly enriched in each phenotype subtype and their enrichment scores (ES).

3. Lists top 20 core genes enriched in each significant gene set and their enrichment scores (ES).

4. Checks if the top core genes are up-regulated or down-regulated.

5. Checks if the top core genes are high expressed or low expressed.

6. Checks if the top core genes are significantly differently expressed genes.

Summary

Table 1. Get Full Table basic data info

basic data info
Number of Gene Sets: 192
Number of samples: 79
Original number of Gene Sets: 404
Maximum gene set size: 388

Table 2. Get Full Table pheno data info

phenotype info
pheno.type: 1 - 4 :[ clus1 ] 24
pheno.type: 2 - 4 :[ clus2 ] 14
pheno.type: 3 - 4 :[ clus3 ] 18
pheno.type: 4 - 4 :[ clus4 ] 23

For the expression subtypes of 17733 genes in 80 samples, GSEA found enriched gene sets in each cluster using 79 gene sets in MSigDB canonical pathways. Top enriched gene sets are listed as below.

- clus1

- Top enriched gene sets are BIOCARTA G1 PATHWAY, BIOCARTA MPR PATHWAY, KEGG PYRIMIDINE METABOLISM, KEGG LYSINE DEGRADATION, KEGG SELENOAMINO ACID METABOLISM, KEGG PYRUVATE METABOLISM, KEGG RIBOSOME, KEGG RNA DEGRADATION, KEGG RNA POLYMERASE, KEGG DNA REPLICATION

- And common core enriched genes are IFNG, POMP, PSMA1, PSMA3, PSMA4, PSMA5, PSMA6, PSMA8, PSMB1, PSMB11

- clus2

- Top enriched gene sets are BIOCARTA NO1 PATHWAY, BIOCARTA AGR PATHWAY, BIOCARTA ALK PATHWAY, BIOCARTA VIP PATHWAY, BIOCARTA CHREBP2 PATHWAY, BIOCARTA WNT PATHWAY, KEGG CYSTEINE AND METHIONINE METABOLISM, KEGG GLYCOSAMINOGLYCAN BIOSYNTHESIS HEPARAN SULFATE, KEGG MAPK SIGNALING PATHWAY, KEGG WNT SIGNALING PATHWAY

- And common core enriched genes are CTNNB1, LEF1, BMP4, APC, BTRC, CCND1, CREBBP, CSNK1A1, FRAT1, FZD1

- clus3

- Top enriched gene sets are BIOCARTA AT1R PATHWAY, BIOCARTA EGF PATHWAY, BIOCARTA GH PATHWAY, BIOCARTA PYK2 PATHWAY, BIOCARTA CHREBP2 PATHWAY, BIOCARTA CREB PATHWAY, KEGG PENTOSE PHOSPHATE PATHWAY, KEGG STEROID HORMONE BIOSYNTHESIS, KEGG O GLYCAN BIOSYNTHESIS, KEGG BUTANOATE METABOLISM

- And common core enriched genes are CUL4A, CUL4B, ERCC8, CCNH, CDK7, ERCC2, ERCC4, ERCC5, GTF2H2, GTF2H3

- clus4

- Top enriched gene sets are BIOCARTA BIOPEPTIDES PATHWAY, BIOCARTA CARM ER PATHWAY, BIOCARTA HDAC PATHWAY, BIOCARTA EGF PATHWAY, BIOCARTA FCER1 PATHWAY, BIOCARTA GH PATHWAY, BIOCARTA IL2RB PATHWAY, BIOCARTA GSK3 PATHWAY, BIOCARTA DEATH PATHWAY, BIOCARTA KERATINOCYTE PATHWAY

- And common core enriched genes are PIK3CG, PIK3R1, PTPN6, STAT5A, NFATC2, BCL2, FAS, FASLG, IKZF3, IL2RA

Results
Subtype clus1 enriched pathways

Table 3. Get Full Table This table shows top 10 pathways which are significantly enriched in cluster clus1. It displays only significant gene sets satisfying nom.p.val.threshold (-1), fwer.p.val.threshold (-1) , fdr.q.val.threshold (0.25) and the default table is sorted by Normalized Enrichment Score (NES). Further details on NES statistics, please visit The Broad GSEA website.

GeneSet(GS) | Size(#genes) | genes.ES.table | ES | NES | NOM.p.val | FDR.q.val | FWER.p.val | Tag.. | Gene.. | Signal | FDR..median. | glob.p.val
--- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | ---
BIOCARTA G1 PATHWAY | 27 | genes.ES.table | 0.49 | 1.4 | 0.18 | 0.64 | 0.95 | 0.48 | 0.3 | 0.34 | 0.52 | 0.19
BIOCARTA MPR PATHWAY | 32 | genes.ES.table | 0.43 | 1.4 | 0.12 | 0.58 | 0.95 | 0.41 | 0.18 | 0.33 | 0.47 | 0.15
KEGG PYRIMIDINE METABOLISM | 97 | genes.ES.table | 0.28 | 1.2 | 0.23 | 0.89 | 1 | 0.26 | 0.16 | 0.22 | 0.78 | 0.35
KEGG LYSINE DEGRADATION | 42 | genes.ES.table | 0.22 | 0.98 | 0.44 | 1 | 1 | 0.17 | 0.12 | 0.15 | 1 | 0.66
KEGG SELENOAMINO ACID METABOLISM | 25 | genes.ES.table | 0.38 | 1.2 | 0.26 | 0.84 | 1 | 0.28 | 0.13 | 0.24 | 0.74 | 0.3
KEGG PYRUVATE METABOLISM | 37 | genes.ES.table | 0.31 | 0.98 | 0.47 | 1 | 1 | 0.24 | 0.17 | 0.2 | 1 | 0.71
KEGG RIBOSOME | 84 | genes.ES.table | 0.57 | 1.6 | 0.075 | 0.41 | 0.68 | 0.73 | 0.29 | 0.52 | 0.26 | 0.11
KEGG RNA DEGRADATION | 56 | genes.ES.table | 0.29 | 1.4 | 0.12 | 0.5 | 0.9 | 0.38 | 0.26 | 0.28 | 0.38 | 0.11
KEGG RNA POLYMERASE | 28 | genes.ES.table | 0.31 | 1.2 | 0.26 | 0.9 | 1 | 0.46 | 0.28 | 0.34 | 0.79 | 0.36
KEGG DNA REPLICATION | 35 | genes.ES.table | 0.57 | 1.5 | 0.14 | 0.53 | 0.87 | 0.54 | 0.22 | 0.42 | 0.4 | 0.14

genes ES table in pathway: BIOCARTA G1 PATHWAY

Table S1. Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank | GENE | SYMBOL | DESC | LIST.LOC | S2N | RES | CORE_ENRICHMENT
--- | --- | --- | --- | --- | --- | --- | ---
1 | PSME4 | PSME4 | PSME4 | 1376 | 0.22 | -0.01 | YES
2 | PSMD4 | PSMD4 | PSMD4 | 1650 | 0.2 | 0.034 | YES
3 | PSMB9 | PSMB9 | PSMB9 | 1983 | 0.18 | 0.068 | YES
4 | PSMD13 | PSMD13 | PSMD13 | 2328 | 0.16 | 0.095 | YES
5 | PSMC3 | PSMC3 | PSMC3 | 2489 | 0.15 | 0.13 | YES
6 | PSMD1 | PSMD1 | PSMD1 | 2660 | 0.14 | 0.16 | YES
7 | PSMA8 | PSMA8 | PSMA8 | 2734 | 0.14 | 0.2 | YES
8 | PSMB4 | PSMB4 | PSMB4 | 2757 | 0.13 | 0.24 | YES
9 | PSMD14 | PSMD14 | PSMD14 | 2916 | 0.13 | 0.27 | YES
10 | PSMC1 | PSMC1 | PSMC1 | 3248 | 0.12 | 0.28 | YES
11 | PSMC5 | PSMC5 | PSMC5 | 3270 | 0.11 | 0.32 | YES
12 | PSMA4 | PSMA4 | PSMA4 | 3457 | 0.11 | 0.34 | YES
13 | PSME2 | PSME2 | PSME2 | 3463 | 0.11 | 0.37 | YES
14 | PSMD11 | PSMD11 | PSMD11 | 3532 | 0.1 | 0.4 | YES
15 | PSMA1 | PSMA1 | PSMA1 | 3842 | 0.095 | 0.41 | YES
16 | PSMB5 | PSMB5 | PSMB5 | 3913 | 0.092 | 0.43 | YES
17 | PSMB3 | PSMB3 | PSMB3 | 4061 | 0.088 | 0.45 | YES
18 | PSMA5 | PSMA5 | PSMA5 | 4206 | 0.084 | 0.47 | YES
19 | PSMD2 | PSMD2 | PSMD2 | 4300 | 0.081 | 0.49 | YES
20 | PSMB11 | PSMB11 | PSMB11 | 4623 | 0.072 | 0.49 | YES
21 | PSMD12 | PSMD12 | PSMD12 | 4875 | 0.065 | 0.5 | YES
22 | PSMB7 | PSMB7 | PSMB7 | 5071 | 0.06 | 0.5 | YES
23 | POMP | POMP | POMP | 5259 | 0.056 | 0.51 | YES
24 | PSMA6 | PSMA6 | PSMA6 | 5425 | 0.052 | 0.52 | YES
25 | PSMC6 | PSMC6 | PSMC6 | 5427 | 0.052 | 0.53 | YES
26 | PSMB1 | PSMB1 | PSMB1 | 5759 | 0.043 | 0.52 | YES
27 | PSMA3 | PSMA3 | PSMA3 | 5824 | 0.041 | 0.53 | YES
28 | PSME3 | PSME3 | PSME3 | 6028 | 0.036 | 0.53 | YES
29 | PSMD3 | PSMD3 | PSMD3 | 6039 | 0.036 | 0.54 | YES
30 | PSMC4 | PSMC4 | PSMC4 | 6156 | 0.034 | 0.55 | YES
31 | PSMD6 | PSMD6 | PSMD6 | 6170 | 0.033 | 0.56 | YES
32 | PSME1 | PSME1 | PSME1 | 6256 | 0.031 | 0.56 | YES
33 | IFNG | IFNG | IFNG | 6322 | 0.029 | 0.57 | YES
34 | PSMB6 | PSMB6 | PSMB6 | 6329 | 0.029 | 0.57 | YES
35 | PSMB2 | PSMB2 | PSMB2 | 6872 | 0.017 | 0.55 | NO
36 | PSMA7 | PSMA7 | PSMA7 | 7461 | 0.0041 | 0.52 | NO
37 | PSMA2 | PSMA2 | PSMA2 | 7554 | 0.0021 | 0.51 | NO
38 | PSMF1 | PSMF1 | PSMF1 | 8465 | -0.018 | 0.47 | NO
39 | PSMB8 | PSMB8 | PSMB8 | 8609 | -0.021 | 0.46 | NO
40 | PSMD7 | PSMD7 | PSMD7 | 8689 | -0.023 | 0.47 | NO
41 | PSMD8 | PSMD8 | PSMD8 | 8968 | -0.029 | 0.46 | NO
42 | PSMC2 | PSMC2 | PSMC2 | 9757 | -0.049 | 0.43 | NO
43 | SHFM1 | SHFM1 | SHFM1 | 10522 | -0.068 | 0.41 | NO

Figure S1. Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: BIOCARTA G1 PATHWAY.

Figure S2. Get High-res Image For the top 5 core enriched genes in the pathway: BIOCARTA G1 PATHWAY, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: BIOCARTA MPR PATHWAY

Table S2. Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank | GENE | SYMBOL | DESC | LIST.LOC | S2N | RES | CORE_ENRICHMENT
--- | --- | --- | --- | --- | --- | --- | ---
1 | POLE2 | POLE2 | POLE2 | 347 | 0.41 | 0.089 | YES
2 | NEIL1 | NEIL1 | NEIL1 | 613 | 0.33 | 0.16 | YES
3 | FEN1 | FEN1 | FEN1 | 687 | 0.32 | 0.24 | YES
4 | NEIL3 | NEIL3 | NEIL3 | 734 | 0.31 | 0.32 | YES
5 | POLE4 | POLE4 | POLE4 | 1451 | 0.22 | 0.34 | YES
6 | MUTYH | MUTYH | MUTYH | 2039 | 0.17 | 0.35 | YES
7 | POLD3 | POLD3 | POLD3 | 2402 | 0.15 | 0.37 | YES
8 | POLD1 | POLD1 | POLD1 | 2471 | 0.15 | 0.41 | YES
9 | PARP1 | PARP1 | PARP1 | 2762 | 0.13 | 0.43 | YES
10 | NTHL1 | NTHL1 | NTHL1 | 2871 | 0.13 | 0.46 | YES
11 | POLD2 | POLD2 | POLD2 | 3619 | 0.1 | 0.44 | YES
12 | PARP2 | PARP2 | PARP2 | 3869 | 0.094 | 0.45 | YES
13 | OGG1 | OGG1 | OGG1 | 4185 | 0.085 | 0.46 | YES
14 | POLB | POLB | POLB | 4561 | 0.073 | 0.45 | YES
15 | APEX1 | APEX1 | APEX1 | 4621 | 0.072 | 0.47 | YES
16 | TDG | TDG | TDG | 4741 | 0.069 | 0.48 | YES
17 | LIG1 | LIG1 | LIG1 | 5040 | 0.061 | 0.48 | YES
18 | POLE3 | POLE3 | POLE3 | 5258 | 0.056 | 0.48 | YES
19 | PCNA | PCNA | PCNA | 6243 | 0.032 | 0.44 | NO
20 | POLD4 | POLD4 | POLD4 | 6406 | 0.027 | 0.43 | NO
21 | MPG | MPG | MPG | 6529 | 0.024 | 0.43 | NO
22 | POLE | POLE | POLE | 6826 | 0.018 | 0.42 | NO
23 | SMUG1 | SMUG1 | SMUG1 | 7820 | -0.004 | 0.37 | NO
24 | MBD4 | MBD4 | MBD4 | 8024 | -0.0082 | 0.36 | NO
25 | POLL | POLL | POLL | 8394 | -0.017 | 0.34 | NO
26 | XRCC1 | XRCC1 | XRCC1 | 9523 | -0.043 | 0.29 | NO
27 | UNG | UNG | UNG | 9915 | -0.053 | 0.28 | NO
28 | LIG3 | LIG3 | LIG3 | 10004 | -0.055 | 0.29 | NO
29 | NEIL2 | NEIL2 | NEIL2 | 10762 | -0.074 | 0.27 | NO
30 | PARP3 | PARP3 | PARP3 | 10782 | -0.074 | 0.28 | NO
31 | PARP4 | PARP4 | PARP4 | 11490 | -0.093 | 0.27 | NO
32 | APEX2 | APEX2 | APEX2 | 15978 | -0.31 | 0.098 | NO

Figure S3. Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: BIOCARTA MPR PATHWAY.

Figure S4. Get High-res Image For the top 5 core enriched genes in the pathway: BIOCARTA MPR PATHWAY, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: KEGG PYRIMIDINE METABOLISM

Table S3. Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank | GENE | SYMBOL | DESC | LIST.LOC | S2N | RES | CORE_ENRICHMENT
--- | --- | --- | --- | --- | --- | --- | ---
1 | RPL21 | RPL21 | RPL21 | 446 | 0.38 | 0.022 | YES
2 | RPS27A | RPS27A | RPS27A | 1532 | 0.21 | -0.014 | YES
3 | RPS7 | RPS7 | RPS7 | 1694 | 0.2 | 0.0018 | YES
4 | RPL37A | RPL37A | RPL37A | 1726 | 0.19 | 0.024 | YES
5 | RPL27A | RPL27A | RPL27A | 1760 | 0.19 | 0.046 | YES
6 | RPL27 | RPL27 | RPL27 | 1891 | 0.18 | 0.061 | YES
7 | RPL23A | RPL23A | RPL23A | 2104 | 0.17 | 0.07 | YES
8 | RPS3 | RPS3 | RPS3 | 2214 | 0.16 | 0.084 | YES
9 | RPL31 | RPL31 | RPL31 | 2312 | 0.16 | 0.098 | YES
10 | RPS25 | RPS25 | RPS25 | 2368 | 0.15 | 0.11 | YES
11 | RPS18 | RPS18 | RPS18 | 2411 | 0.15 | 0.13 | YES
12 | RPL17 | RPL17 | RPL17 | 2456 | 0.15 | 0.15 | YES
13 | RPLP2 | RPLP2 | RPLP2 | 2540 | 0.14 | 0.16 | YES
14 | RPS29 | RPS29 | RPS29 | 2715 | 0.14 | 0.17 | YES
15 | RPSA | RPSA | RPSA | 2849 | 0.13 | 0.18 | YES
16 | RPS13 | RPS13 | RPS13 | 2859 | 0.13 | 0.19 | YES
17 | RPS19 | RPS19 | RPS19 | 2868 | 0.13 | 0.21 | YES
18 | RPS12 | RPS12 | RPS12 | 2925 | 0.13 | 0.22 | YES
19 | RPS24 | RPS24 | RPS24 | 2954 | 0.13 | 0.23 | YES
20 | RPL36 | RPL36 | RPL36 | 2974 | 0.12 | 0.25 | YES
21 | RPLP1 | RPLP1 | RPLP1 | 2990 | 0.12 | 0.26 | YES
22 | RPS17 | RPS17 | RPS17 | 3027 | 0.12 | 0.28 | YES
23 | FAU | FAU | FAU | 3183 | 0.12 | 0.28 | YES
24 | RPL29 | RPL29 | RPL29 | 3247 | 0.12 | 0.29 | YES
25 | RPL22 | RPL22 | RPL22 | 3374 | 0.11 | 0.3 | YES
26 | RPS8 | RPS8 | RPS8 | 3415 | 0.11 | 0.31 | YES
27 | RPL18A | RPL18A | RPL18A | 3454 | 0.11 | 0.32 | YES
28 | RPL4 | RPL4 | RPL4 | 3459 | 0.11 | 0.34 | YES
29 | RPL35 | RPL35 | RPL35 | 3533 | 0.1 | 0.34 | YES
30 | RPS10 | RPS10 | RPS10 | 3548 | 0.1 | 0.36 | YES
31 | RPL32 | RPL32 | RPL32 | 3653 | 0.1 | 0.36 | YES
32 | RPS9 | RPS9 | RPS9 | 3655 | 0.1 | 0.38 | YES
33 | RPLP0 | RPLP0 | RPLP0 | 3724 | 0.099 | 0.38 | YES
34 | RPL11 | RPL11 | RPL11 | 3795 | 0.096 | 0.39 | YES
35 | RPS2 | RPS2 | RPS2 | 3875 | 0.094 | 0.4 | YES
36 | RPL22L1 | RPL22L1 | RPL22L1 | 3924 | 0.092 | 0.41 | YES
37 | RPL14 | RPL14 | RPL14 | 3983 | 0.091 | 0.42 | YES
38 | RPL35A | RPL35A | RPL35A | 3987 | 0.091 | 0.43 | YES
39 | RPL13A | RPL13A | RPL13A | 4140 | 0.086 | 0.43 | YES
40 | RPS27 | RPS27 | RPS27 | 4182 | 0.085 | 0.44 | YES
41 | RPL23 | RPL23 | RPL23 | 4220 | 0.084 | 0.44 | YES
42 | RPL8 | RPL8 | RPL8 | 4290 | 0.082 | 0.45 | YES
43 | RPL30 | RPL30 | RPL30 | 4293 | 0.082 | 0.46 | YES
44 | RPS20 | RPS20 | RPS20 | 4315 | 0.081 | 0.47 | YES
45 | RPS16 | RPS16 | RPS16 | 4332 | 0.08 | 0.48 | YES
46 | RPL12 | RPL12 | RPL12 | 4379 | 0.079 | 0.49 | YES
47 | RPL26 | RPL26 | RPL26 | 4544 | 0.074 | 0.49 | YES
48 | RPL19 | RPL19 | RPL19 | 4565 | 0.073 | 0.5 | YES
49 | RPS11 | RPS11 | RPS11 | 4597 | 0.072 | 0.5 | YES
50 | UBA52 | UBA52 | UBA52 | 4612 | 0.072 | 0.51 | YES
51 | RPL5 | RPL5 | RPL5 | 4634 | 0.072 | 0.52 | YES
52 | RPL24 | RPL24 | RPL24 | 4668 | 0.071 | 0.52 | YES
53 | RPS26 | RPS26 | RPS26 | 4736 | 0.069 | 0.53 | YES
54 | RPL3 | RPL3 | RPL3 | 4831 | 0.066 | 0.53 | YES
55 | RPS15 | RPS15 | RPS15 | 4845 | 0.066 | 0.54 | YES
56 | RPL28 | RPL28 | RPL28 | 4862 | 0.066 | 0.55 | YES
57 | RPL10A | RPL10A | RPL10A | 4930 | 0.064 | 0.55 | YES
58 | RPL38 | RPL38 | RPL38 | 4979 | 0.062 | 0.56 | YES
59 | RPL7 | RPL7 | RPL7 | 5008 | 0.062 | 0.56 | YES
60 | RPL36AL | RPL36AL | RPL36AL | 5086 | 0.06 | 0.57 | YES
61 | RPL7A | RPL7A | RPL7A | 5145 | 0.059 | 0.57 | YES
62 | RPS3A | RPS3A | RPS3A | 5454 | 0.051 | 0.56 | NO
63 | RPS15A | RPS15A | RPS15A | 5465 | 0.051 | 0.56 | NO
64 | RPL13 | RPL13 | RPL13 | 5603 | 0.047 | 0.56 | NO
65 | RPL15 | RPL15 | RPL15 | 5625 | 0.046 | 0.57 | NO
66 | RPS5 | RPS5 | RPS5 | 5701 | 0.044 | 0.57 | NO
67 | RPL41 | RPL41 | RPL41 | 5783 | 0.042 | 0.57 | NO
68 | RPS21 | RPS21 | RPS21 | 6403 | 0.027 | 0.54 | NO
69 | RPS6 | RPS6 | RPS6 | 6663 | 0.022 | 0.52 | NO
70 | RPL37 | RPL37 | RPL37 | 6817 | 0.018 | 0.52 | NO
71 | MRPL13 | MRPL13 | MRPL13 | 6880 | 0.017 | 0.52 | NO
72 | RPL39 | RPL39 | RPL39 | 7139 | 0.011 | 0.5 | NO
73 | RPL6 | RPL6 | RPL6 | 7234 | 0.0091 | 0.5 | NO
74 | RSL24D1 | RSL24D1 | RSL24D1 | 7518 | 0.003 | 0.48 | NO
75 | RPS4X | RPS4X | RPS4X | 7716 | -0.0016 | 0.47 | NO
76 | RPL34 | RPL34 | RPL34 | 8102 | -0.01 | 0.45 | NO
77 | RPL10 | RPL10 | RPL10 | 8258 | -0.014 | 0.45 | NO
78 | RPS27L | RPS27L | RPS27L | 8532 | -0.02 | 0.43 | NO
79 | RPS23 | RPS23 | RPS23 | 8692 | -0.023 | 0.43 | NO
80 | RPS28 | RPS28 | RPS28 | 10647 | -0.071 | 0.32 | NO
81 | RPL26L1 | RPL26L1 | RPL26L1 | 10697 | -0.072 | 0.33 | NO
82 | RPS4Y1 | RPS4Y1 | RPS4Y1 | 11213 | -0.085 | 0.31 | NO
83 | RPL9 | RPL9 | RPL9 | 13932 | -0.18 | 0.18 | NO
84 | RPL36A | RPL36A | RPL36A | 15622 | -0.28 | 0.12 | NO

Figure S5. Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: KEGG PYRIMIDINE METABOLISM.

Figure S6. Get High-res Image For the top 5 core enriched genes in the pathway: KEGG PYRIMIDINE METABOLISM, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: KEGG LYSINE DEGRADATION

Table S4. Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank | GENE | SYMBOL | DESC | LIST.LOC | S2N | RES | CORE_ENRICHMENT
--- | --- | --- | --- | --- | --- | --- | ---
1 | CDC20 | CDC20 | CDC20 | 83 | 0.57 | 0.026 | YES
2 | CDC25A | CDC25A | CDC25A | 109 | 0.54 | 0.054 | YES
3 | BUB1 | BUB1 | BUB1 | 128 | 0.53 | 0.082 | YES
4 | CDC45 | CDC45 | CDC45 | 130 | 0.52 | 0.11 | YES
5 | E2F2 | E2F2 | E2F2 | 135 | 0.52 | 0.14 | YES
6 | ORC1L | ORC1L | ORC1L | 263 | 0.44 | 0.16 | YES
7 | PLK1 | PLK1 | PLK1 | 285 | 0.43 | 0.18 | YES
8 | CCNB2 | CCNB2 | CCNB2 | 298 | 0.42 | 0.2 | YES
9 | BUB1B | BUB1B | BUB1B | 351 | 0.4 | 0.22 | YES
10 | CDK1 | CDK1 | CDK1 | 365 | 0.4 | 0.24 | YES
11 | CDC7 | CDC7 | CDC7 | 469 | 0.37 | 0.25 | YES
12 | PTTG1 | PTTG1 | PTTG1 | 470 | 0.37 | 0.27 | YES
13 | CCNA2 | CCNA2 | CCNA2 | 505 | 0.36 | 0.29 | YES
14 | PKMYT1 | PKMYT1 | PKMYT1 | 590 | 0.34 | 0.3 | YES
15 | CDC25C | CDC25C | CDC25C | 751 | 0.31 | 0.31 | YES
16 | CCNE2 | CCNE2 | CCNE2 | 779 | 0.3 | 0.33 | YES
17 | TTK | TTK | TTK | 781 | 0.3 | 0.34 | YES
18 | CHEK2 | CHEK2 | CHEK2 | 920 | 0.28 | 0.35 | YES
19 | CHEK1 | CHEK1 | CHEK1 | 959 | 0.28 | 0.36 | YES
20 | ESPL1 | ESPL1 | ESPL1 | 997 | 0.27 | 0.38 | YES
21 | CDC6 | CDC6 | CDC6 | 1019 | 0.27 | 0.39 | YES
22 | CDK6 | CDK6 | CDK6 | 1021 | 0.27 | 0.4 | YES
23 | MCM6 | MCM6 | MCM6 | 1046 | 0.26 | 0.42 | YES
24 | MYC | MYC | MYC | 1117 | 0.25 | 0.43 | YES
25 | MCM2 | MCM2 | MCM2 | 1182 | 0.25 | 0.44 | YES
26 | TGFB2 | TGFB2 | TGFB2 | 1233 | 0.24 | 0.45 | YES
27 | MCM5 | MCM5 | MCM5 | 1270 | 0.24 | 0.46 | YES
28 | SFN | SFN | SFN | 1288 | 0.23 | 0.47 | YES
29 | GADD45A | GADD45A | GADD45A | 1476 | 0.21 | 0.47 | YES
30 | SKP2 | SKP2 | SKP2 | 1495 | 0.21 | 0.48 | YES
31 | CCNB1 | CCNB1 | CCNB1 | 1566 | 0.21 | 0.49 | YES
32 | MCM7 | MCM7 | MCM7 | 1634 | 0.2 | 0.5 | YES
33 | RBX1 | RBX1 | RBX1 | 2125 | 0.17 | 0.48 | YES
34 | ORC2L | ORC2L | ORC2L | 2184 | 0.16 | 0.48 | YES
35 | SMC1B | SMC1B | SMC1B | 2385 | 0.15 | 0.48 | YES
36 | YWHAH | YWHAH | YWHAH | 2515 | 0.14 | 0.48 | YES
37 | CDKN2C | CDKN2C | CDKN2C | 2643 | 0.14 | 0.48 | YES
38 | MCM4 | MCM4 | MCM4 | 2694 | 0.14 | 0.48 | YES
39 | MAD2L2 | MAD2L2 | MAD2L2 | 2780 | 0.13 | 0.49 | YES
40 | CCND1 | CCND1 | CCND1 | 2782 | 0.13 | 0.49 | YES
41 | ORC6L | ORC6L | ORC6L | 3016 | 0.12 | 0.49 | YES
42 | SMAD3 | SMAD3 | SMAD3 | 3021 | 0.12 | 0.49 | YES
43 | SMAD2 | SMAD2 | SMAD2 | 3060 | 0.12 | 0.5 | YES
44 | ANAPC1 | ANAPC1 | ANAPC1 | 3099 | 0.12 | 0.5 | YES
45 | MCM3 | MCM3 | MCM3 | 3110 | 0.12 | 0.51 | YES
46 | MAD1L1 | MAD1L1 | MAD1L1 | 3189 | 0.12 | 0.51 | YES
47 | WEE1 | WEE1 | WEE1 | 3241 | 0.12 | 0.51 | YES
48 | CDC25B | CDC25B | CDC25B | 3272 | 0.11 | 0.52 | YES
49 | BUB3 | BUB3 | BUB3 | 3379 | 0.11 | 0.52 | YES
50 | E2F1 | E2F1 | E2F1 | 3398 | 0.11 | 0.52 | YES
51 | ANAPC11 | ANAPC11 | ANAPC11 | 3430 | 0.11 | 0.53 | YES
52 | CDC26 | CDC26 | CDC26 | 3732 | 0.099 | 0.52 | NO
53 | HDAC2 | HDAC2 | HDAC2 | 3754 | 0.098 | 0.52 | NO
54 | ORC4L | ORC4L | ORC4L | 3852 | 0.095 | 0.52 | NO
55 | YWHAQ | YWHAQ | YWHAQ | 3877 | 0.094 | 0.52 | NO
56 | MAD2L1 | MAD2L1 | MAD2L1 | 4086 | 0.088 | 0.52 | NO
57 | CDKN1C | CDKN1C | CDKN1C | 4343 | 0.08 | 0.5 | NO
58 | CDKN2A | CDKN2A | CDKN2A | 4437 | 0.077 | 0.5 | NO
59 | TFDP1 | TFDP1 | TFDP1 | 4472 | 0.076 | 0.51 | NO
60 | SMAD4 | SMAD4 | SMAD4 | 4814 | 0.067 | 0.49 | NO
61 | TGFB3 | TGFB3 | TGFB3 | 5229 | 0.056 | 0.47 | NO
62 | PRKDC | PRKDC | PRKDC | 5251 | 0.056 | 0.47 | NO
63 | CDK2 | CDK2 | CDK2 | 5385 | 0.053 | 0.47 | NO
64 | ZBTB17 | ZBTB17 | ZBTB17 | 5435 | 0.052 | 0.47 | NO
65 | CDKN2D | CDKN2D | CDKN2D | 5463 | 0.051 | 0.47 | NO
66 | CCNE1 | CCNE1 | CCNE1 | 6213 | 0.032 | 0.43 | NO
67 | PCNA | PCNA | PCNA | 6243 | 0.032 | 0.43 | NO
68 | CDKN1A | CDKN1A | CDKN1A | 6292 | 0.03 | 0.43 | NO
69 | MDM2 | MDM2 | MDM2 | 6349 | 0.029 | 0.42 | NO
70 | CDC16 | CDC16 | CDC16 | 6455 | 0.026 | 0.42 | NO
71 | ANAPC7 | ANAPC7 | ANAPC7 | 6541 | 0.024 | 0.42 | NO
72 | TGFB1 | TGFB1 | TGFB1 | 6567 | 0.024 | 0.42 | NO
73 | ORC3L | ORC3L | ORC3L | 6893 | 0.016 | 0.4 | NO
74 | SMC3 | SMC3 | SMC3 | 6983 | 0.014 | 0.4 | NO
75 | TFDP2 | TFDP2 | TFDP2 | 7109 | 0.012 | 0.39 | NO
76 | CDK4 | CDK4 | CDK4 | 7239 | 0.0089 | 0.38 | NO
77 | TP53 | TP53 | TP53 | 7338 | 0.0068 | 0.38 | NO
78 | YWHAZ | YWHAZ | YWHAZ | 7370 | 0.0061 | 0.38 | NO
79 | YWHAE | YWHAE | YWHAE | 7472 | 0.0038 | 0.37 | NO
80 | CDC27 | CDC27 | CDC27 | 7522 | 0.0029 | 0.37 | NO
81 | HDAC1 | HDAC1 | HDAC1 | 7532 | 0.0027 | 0.37 | NO
82 | PTTG2 | PTTG2 | PTTG2 | 7572 | 0.0017 | 0.36 | NO
83 | E2F5 | E2F5 | E2F5 | 7675 | -0.0004 | 0.36 | NO
84 | E2F4 | E2F4 | E2F4 | 8061 | -0.0093 | 0.34 | NO
85 | CCND3 | CCND3 | CCND3 | 8164 | -0.012 | 0.33 | NO
86 | GSK3B | GSK3B | GSK3B | 8169 | -0.012 | 0.33 | NO
87 | ANAPC2 | ANAPC2 | ANAPC2 | 8293 | -0.014 | 0.33 | NO
88 | ATM | ATM | ATM | 8503 | -0.019 | 0.32 | NO
89 | ABL1 | ABL1 | ABL1 | 8542 | -0.02 | 0.31 | NO
90 | ANAPC5 | ANAPC5 | ANAPC5 | 8543 | -0.02 | 0.32 | NO
91 | RAD21 | RAD21 | RAD21 | 8761 | -0.024 | 0.3 | NO
92 | SMC1A | SMC1A | SMC1A | 8816 | -0.026 | 0.3 | NO
93 | ANAPC10 | ANAPC10 | ANAPC10 | 8944 | -0.028 | 0.3 | NO
94 | FZR1 | FZR1 | FZR1 | 9079 | -0.032 | 0.29 | NO
95 | CCNA1 | CCNA1 | CCNA1 | 9427 | -0.041 | 0.27 | NO
96 | ATR | ATR | ATR | 9603 | -0.045 | 0.27 | NO
97 | CDC14A | CDC14A | CDC14A | 9684 | -0.047 | 0.26 | NO
98 | YWHAB | YWHAB | YWHAB | 9778 | -0.05 | 0.26 | NO
99 | EP300 | EP300 | EP300 | 9891 | -0.052 | 0.26 | NO
100 | CCNB3 | CCNB3 | CCNB3 | 10017 | -0.055 | 0.25 | NO
101 | ORC5L | ORC5L | ORC5L | 10091 | -0.057 | 0.25 | NO
102 | ANAPC13 | ANAPC13 | ANAPC13 | 10165 | -0.059 | 0.25 | NO
103 | CUL1 | CUL1 | CUL1 | 10600 | -0.07 | 0.23 | NO
104 | E2F3 | E2F3 | E2F3 | 10696 | -0.072 | 0.23 | NO
105 | CDKN1B | CDKN1B | CDKN1B | 10878 | -0.077 | 0.22 | NO
106 | CDC23 | CDC23 | CDC23 | 11409 | -0.091 | 0.2 | NO
107 | STAG1 | STAG1 | STAG1 | 11500 | -0.093 | 0.2 | NO
108 | CCNH | CCNH | CCNH | 12171 | -0.11 | 0.17 | NO
109 | RB1 | RB1 | RB1 | 12214 | -0.11 | 0.17 | NO
110 | YWHAG | YWHAG | YWHAG | 12323 | -0.12 | 0.17 | NO
111 | CDC14B | CDC14B | CDC14B | 12362 | -0.12 | 0.17 | NO
112 | SKP1 | SKP1 | SKP1 | 12508 | -0.12 | 0.17 | NO
113 | GADD45B | GADD45B | GADD45B | 12597 | -0.13 | 0.18 | NO
114 | ANAPC4 | ANAPC4 | ANAPC4 | 12869 | -0.14 | 0.17 | NO
115 | CREBBP | CREBBP | CREBBP | 12946 | -0.14 | 0.17 | NO
116 | CDK7 | CDK7 | CDK7 | 13380 | -0.15 | 0.15 | NO
117 | STAG2 | STAG2 | STAG2 | 13582 | -0.16 | 0.15 | NO
118 | CDKN2B | CDKN2B | CDKN2B | 13643 | -0.16 | 0.16 | NO
119 | RBL1 | RBL1 | RBL1 | 13913 | -0.18 | 0.15 | NO
120 | GADD45G | GADD45G | GADD45G | 14893 | -0.23 | 0.11 | NO
121 | CCND2 | CCND2 | CCND2 | 15253 | -0.25 | 0.1 | NO
122 | RBL2 | RBL2 | RBL2 | 15586 | -0.27 | 0.096 | NO
123 | WEE2 | WEE2 | WEE2 | 16994 | -0.46 | 0.041 | NO

Figure S7. Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: KEGG LYSINE DEGRADATION.

Figure S8. Get High-res Image For the top 5 core enriched genes in the pathway: KEGG LYSINE DEGRADATION, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: KEGG SELENOAMINO ACID METABOLISM

Table S5. Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank | GENE | SYMBOL | DESC | LIST.LOC | S2N | RES | CORE_ENRICHMENT
--- | --- | --- | --- | --- | --- | --- | ---
1 | HSPA6 | HSPA6 | HSPA6 | 402 | 0.39 | 0.018 | YES
2 | THOC4 | THOC4 | THOC4 | 1165 | 0.25 | 0.00095 | YES
3 | SF3B4 | SF3B4 | SF3B4 | 1350 | 0.23 | 0.014 | YES
4 | SNRPA1 | SNRPA1 | SNRPA1 | 1445 | 0.22 | 0.032 | YES
5 | SNRPG | SNRPG | SNRPG | 1608 | 0.2 | 0.044 | YES
6 | EIF4A3 | EIF4A3 | EIF4A3 | 1627 | 0.2 | 0.064 | YES
7 | SNRPD1 | SNRPD1 | SNRPD1 | 1835 | 0.18 | 0.072 | YES
8 | PHF5A | PHF5A | PHF5A | 1866 | 0.18 | 0.089 | YES
9 | SNRPE | SNRPE | SNRPE | 2531 | 0.14 | 0.067 | YES
10 | SF3B14 | SF3B14 | SF3B14 | 2551 | 0.14 | 0.081 | YES
11 | RBM8A | RBM8A | RBM8A | 2650 | 0.14 | 0.09 | YES
12 | SART1 | SART1 | SART1 | 2657 | 0.14 | 0.1 | YES
13 | PRPF3 | PRPF3 | PRPF3 | 2760 | 0.13 | 0.11 | YES
14 | PRPF40A | PRPF40A | PRPF40A | 2840 | 0.13 | 0.12 | YES
15 | HSPA1B | HSPA1B | HSPA1B | 2922 | 0.13 | 0.13 | YES
16 | SNRPD3 | SNRPD3 | SNRPD3 | 3125 | 0.12 | 0.13 | YES
17 | SNRNP40 | SNRNP40 | SNRNP40 | 3196 | 0.12 | 0.14 | YES
18 | HNRNPA3 | HNRNPA3 | HNRNPA3 | 3246 | 0.12 | 0.15 | YES
19 | PUF60 | PUF60 | PUF60 | 3308 | 0.11 | 0.16 | YES
20 | PRPF38A | PRPF38A | PRPF38A | 3330 | 0.11 | 0.17 | YES
21 | SFRS7 | SFRS7 | SFRS7 | 3527 | 0.1 | 0.17 | YES
22 | SF3B2 | SF3B2 | SF3B2 | 3549 | 0.1 | 0.18 | YES
23 | CCDC12 | CCDC12 | CCDC12 | 3595 | 0.1 | 0.19 | YES
24 | SNRPC | SNRPC | SNRPC | 3632 | 0.1 | 0.2 | YES
25 | LSM2 | LSM2 | LSM2 | 3773 | 0.097 | 0.2 | YES
26 | SNRNP27 | SNRNP27 | SNRNP27 | 3800 | 0.096 | 0.2 | YES
27 | USP39 | USP39 | USP39 | 3876 | 0.094 | 0.21 | YES
28 | LSM4 | LSM4 | LSM4 | 3964 | 0.091 | 0.22 | YES
29 | LSM3 | LSM3 | LSM3 | 3968 | 0.091 | 0.22 | YES
30 | DHX16 | DHX16 | DHX16 | 3986 | 0.091 | 0.23 | YES
31 | SMNDC1 | SMNDC1 | SMNDC1 | 3995 | 0.09 | 0.24 | YES
32 | NHP2L1 | NHP2L1 | NHP2L1 | 4024 | 0.089 | 0.25 | YES
33 | U2AF1 | U2AF1 | U2AF1 | 4040 | 0.089 | 0.26 | YES
34 | PRPF4 | PRPF4 | PRPF4 | 4068 | 0.088 | 0.27 | YES
35 | LSM7 | LSM7 | LSM7 | 4099 | 0.087 | 0.27 | YES
36 | THOC1 | THOC1 | THOC1 | 4166 | 0.085 | 0.28 | YES
37 | SFRS3 | SFRS3 | SFRS3 | 4370 | 0.08 | 0.28 | YES
38 | TXNL4A | TXNL4A | TXNL4A | 4466 | 0.076 | 0.28 | YES
39 | CWC15 | CWC15 | CWC15 | 4477 | 0.076 | 0.29 | YES
40 | SF3A2 | SF3A2 | SF3A2 | 4581 | 0.073 | 0.29 | YES
41 | ISY1 | ISY1 | ISY1 | 4722 | 0.069 | 0.29 | YES
42 | SNRPA | SNRPA | SNRPA | 4732 | 0.069 | 0.29 | YES
43 | SF3B5 | SF3B5 | SF3B5 | 4834 | 0.066 | 0.3 | YES
44 | SF3B1 | SF3B1 | SF3B1 | 4906 | 0.064 | 0.3 | YES
45 | HNRNPU | HNRNPU | HNRNPU | 4929 | 0.064 | 0.3 | YES
46 | HSPA1A | HSPA1A | HSPA1A | 4952 | 0.063 | 0.31 | YES
47 | SFRS2 | SFRS2 | SFRS2 | 4986 | 0.062 | 0.31 | YES
48 | NCBP1 | NCBP1 | NCBP1 | 5107 | 0.06 | 0.31 | YES
49 | SNRNP70 | SNRNP70 | SNRNP70 | 5183 | 0.058 | 0.32 | YES
50 | RBM17 | RBM17 | RBM17 | 5242 | 0.056 | 0.32 | YES
51 | CDC40 | CDC40 | CDC40 | 5453 | 0.051 | 0.31 | YES
52 | TRA2A | TRA2A | TRA2A | 5552 | 0.048 | 0.31 | YES
53 | EFTUD2 | EFTUD2 | EFTUD2 | 5693 | 0.044 | 0.31 | YES
54 | TRA2B | TRA2B | TRA2B | 5702 | 0.044 | 0.31 | YES
55 | SFRS1 | SFRS1 | SFRS1 | 5769 | 0.042 | 0.31 | YES
56 | HSPA1L | HSPA1L | HSPA1L | 5793 | 0.042 | 0.32 | YES
57 | SNW1 | SNW1 | SNW1 | 5814 | 0.041 | 0.32 | YES
58 | BUD31 | BUD31 | BUD31 | 5833 | 0.041 | 0.32 | YES
59 | PCBP1 | PCBP1 | PCBP1 | 5854 | 0.04 | 0.32 | YES
60 | HNRNPM | HNRNPM | HNRNPM | 5887 | 0.039 | 0.33 | YES
61 | SF3A3 | SF3A3 | SF3A3 | 5934 | 0.039 | 0.33 | YES
62 | HNRNPC | HNRNPC | HNRNPC | 5948 | 0.038 | 0.33 | YES
63 | BAT1 | BAT1 | BAT1 | 5966 | 0.038 | 0.34 | YES
64 | PPIE | PPIE | PPIE | 6038 | 0.036 | 0.34 | YES
65 | NAA38 | NAA38 | NAA38 | 6076 | 0.035 | 0.34 | YES
66 | SNRNP200 | SNRNP200 | SNRNP200 | 6090 | 0.035 | 0.34 | YES
67 | SFRS9 | SFRS9 | SFRS9 | 6097 | 0.035 | 0.34 | YES
68 | HNRNPA1 | HNRNPA1 | HNRNPA1 | 6175 | 0.033 | 0.34 | NO
69 | PRPF19 | PRPF19 | PRPF19 | 6299 | 0.03 | 0.34 | NO
70 | SFRS6 | SFRS6 | SFRS6 | 6411 | 0.027 | 0.34 | NO
71 | HNRNPA1L2 | HNRNPA1L2 | HNRNPA1L2 | 6430 | 0.027 | 0.34 | NO
72 | SNRPD2 | SNRPD2 | SNRPD2 | 6436 | 0.026 | 0.34 | NO
73 | SF3A1 | SF3A1 | SF3A1 | 6671 | 0.021 | 0.33 | NO
74 | MAGOH | MAGOH | MAGOH | 6730 | 0.02 | 0.33 | NO
75 | DDX42 | DDX42 | DDX42 | 6752 | 0.02 | 0.33 | NO
76 | SNRPB | SNRPB | SNRPB | 6803 | 0.018 | 0.33 | NO
77 | SNRPF | SNRPF | SNRPF | 6855 | 0.017 | 0.33 | NO
78 | PPIH | PPIH | PPIH | 7147 | 0.011 | 0.31 | NO
79 | LSM6 | LSM6 | LSM6 | 7273 | 0.0082 | 0.3 | NO
80 | HSPA8 | HSPA8 | HSPA8 | 7364 | 0.0062 | 0.3 | NO
81 | LSM5 | LSM5 | LSM5 | 7406 | 0.0051 | 0.3 | NO
82 | CDC5L | CDC5L | CDC5L | 7463 | 0.004 | 0.3 | NO
83 | PPIL1 | PPIL1 | PPIL1 | 7499 | 0.0033 | 0.29 | NO
84 | DHX8 | DHX8 | DHX8 | 7600 | 0.0012 | 0.29 | NO
85 | DDX5 | DDX5 | DDX5 | 7622 | 0.00078 | 0.29 | NO
86 | ACIN1 | ACIN1 | ACIN1 | 7704 | -0.0012 | 0.28 | NO
87 | HNRNPK | HNRNPK | HNRNPK | 7857 | -0.0047 | 0.27 | NO
88 | RBMX | RBMX | RBMX | 8083 | -0.0099 | 0.26 | NO
89 | SFRS13A | SFRS13A | SFRS13A | 8115 | -0.011 | 0.26 | NO
90 | SFRS4 | SFRS4 | SFRS4 | 8167 | -0.012 | 0.26 | NO
91 | CTNNBL1 | CTNNBL1 | CTNNBL1 | 8196 | -0.012 | 0.26 | NO
92 | RBM25 | RBM25 | RBM25 | 8306 | -0.015 | 0.26 | NO
93 | PRPF38B | PRPF38B | PRPF38B | 8320 | -0.015 | 0.26 | NO
94 | PRPF31 | PRPF31 | PRPF31 | 8343 | -0.015 | 0.26 | NO
95 | CHERP | CHERP | CHERP | 8413 | -0.017 | 0.25 | NO
96 | SF3B3 | SF3B3 | SF3B3 | 8548 | -0.02 | 0.25 | NO
97 | XAB2 | XAB2 | XAB2 | 8613 | -0.021 | 0.25 | NO
98 | PRPF8 | PRPF8 | PRPF8 | 8649 | -0.022 | 0.25 | NO
99 | SFRS2B | SFRS2B | SFRS2B | 8725 | -0.024 | 0.25 | NO
100 | PRPF6 | PRPF6 | PRPF6 | 8984 | -0.029 | 0.23 | NO
101 | DDX46 | DDX46 | DDX46 | 9000 | -0.029 | 0.24 | NO
102 | PQBP1 | PQBP1 | PQBP1 | 9057 | -0.031 | 0.24 | NO
103 | BCAS2 | BCAS2 | BCAS2 | 9110 | -0.032 | 0.24 | NO
104 | SYF2 | SYF2 | SYF2 | 9152 | -0.033 | 0.24 | NO
105 | DDX23 | DDX23 | DDX23 | 9246 | -0.036 | 0.24 | NO
106 | SR140 | SR140 | SR140 | 9483 | -0.042 | 0.23 | NO
107 | DHX38 | DHX38 | DHX38 | 9494 | -0.042 | 0.23 | NO
108 | DHX15 | DHX15 | DHX15 | 9573 | -0.044 | 0.23 | NO
109 | U2AF2 | U2AF2 | U2AF2 | 9664 | -0.047 | 0.23 | NO
110 | PRPF18 | PRPF18 | PRPF18 | 9669 | -0.047 | 0.24 | NO
111 | AQR | AQR | AQR | 10566 | -0.069 | 0.19 | NO
112 | WBP11 | WBP11 | WBP11 | 10812 | -0.075 | 0.19 | NO
113 | SNRPB2 | SNRPB2 | SNRPB2 | 11037 | -0.081 | 0.18 | NO
114 | TCERG1 | TCERG1 | TCERG1 | 11051 | -0.081 | 0.19 | NO
115 | SFRS5 | SFRS5 | SFRS5 | 11237 | -0.086 | 0.19 | NO
116 | ZMAT2 | ZMAT2 | ZMAT2 | 11428 | -0.091 | 0.19 | NO
117 | RBM22 | RBM22 | RBM22 | 11684 | -0.099 | 0.18 | NO
118 | MAGOHB | MAGOHB | MAGOHB | 11729 | -0.1 | 0.19 | NO
119 | PLRG1 | PLRG1 | PLRG1 | 12062 | -0.11 | 0.18 | NO
120 | PRPF40B | PRPF40B | PRPF40B | 12211 | -0.11 | 0.19 | NO
121 | CRNKL1 | CRNKL1 | CRNKL1 | 12482 | -0.12 | 0.18 | NO
122 | SLU7 | SLU7 | SLU7 | 12873 | -0.14 | 0.18 | NO
123 | THOC3 | THOC3 | THOC3 | 13220 | -0.15 | 0.17 | NO
124 | THOC2 | THOC2 | THOC2 | 13726 | -0.17 | 0.16 | NO
125 | HSPA2 | HSPA2 | HSPA2 | 17472 | -0.62 | 0.014 | NO

Figure S9. Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: KEGG SELENOAMINO ACID METABOLISM.

Figure S10. Get High-res Image For the top 5 core enriched genes in the pathway: KEGG SELENOAMINO ACID METABOLISM, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: KEGG PYRUVATE METABOLISM

Table S6. Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank | GENE | SYMBOL | DESC | LIST.LOC | S2N | RES | CORE_ENRICHMENT
--- | --- | --- | --- | --- | --- | --- | ---
1 | POLE2 | POLE2 | POLE2 | 347 | 0.41 | 0.069 | YES
2 | DNA2 | DNA2 | DNA2 | 652 | 0.32 | 0.12 | YES
3 | FEN1 | FEN1 | FEN1 | 687 | 0.32 | 0.19 | YES
4 | MCM6 | MCM6 | MCM6 | 1046 | 0.26 | 0.23 | YES
5 | MCM2 | MCM2 | MCM2 | 1182 | 0.25 | 0.27 | YES
6 | MCM5 | MCM5 | MCM5 | 1270 | 0.24 | 0.32 | YES
7 | POLE4 | POLE4 | POLE4 | 1451 | 0.22 | 0.36 | YES
8 | MCM7 | MCM7 | MCM7 | 1634 | 0.2 | 0.39 | YES
9 | RNASEH1 | RNASEH1 | RNASEH1 | 1849 | 0.18 | 0.42 | YES
10 | POLA2 | POLA2 | POLA2 | 2264 | 0.16 | 0.43 | YES
11 | POLD3 | POLD3 | POLD3 | 2402 | 0.15 | 0.45 | YES
12 | POLD1 | POLD1 | POLD1 | 2471 | 0.15 | 0.48 | YES
13 | MCM4 | MCM4 | MCM4 | 2694 | 0.14 | 0.5 | YES
14 | RFC4 | RFC4 | RFC4 | 2777 | 0.13 | 0.52 | YES
15 | MCM3 | MCM3 | MCM3 | 3110 | 0.12 | 0.53 | YES
16 | RFC2 | RFC2 | RFC2 | 3302 | 0.11 | 0.54 | YES
17 | PRIM2 | PRIM2 | PRIM2 | 3564 | 0.1 | 0.55 | YES
18 | POLD2 | POLD2 | POLD2 | 3619 | 0.1 | 0.57 | YES
19 | PRIM1 | PRIM1 | PRIM1 | 3936 | 0.092 | 0.57 | YES
20 | RNASEH2A | RNASEH2A | RNASEH2A | 4529 | 0.074 | 0.55 | NO
21 | RFC3 | RFC3 | RFC3 | 4738 | 0.069 | 0.56 | NO
22 | LIG1 | LIG1 | LIG1 | 5040 | 0.061 | 0.55 | NO
23 | POLE3 | POLE3 | POLE3 | 5258 | 0.056 | 0.55 | NO
24 | RNASEH2B | RNASEH2B | RNASEH2B | 6223 | 0.032 | 0.5 | NO
25 | PCNA | PCNA | PCNA | 6243 | 0.032 | 0.51 | NO
26 | POLD4 | POLD4 | POLD4 | 6406 | 0.027 | 0.51 | NO
27 | RNASEH2C | RNASEH2C | RNASEH2C | 6655 | 0.022 | 0.5 | NO
28 | RFC5 | RFC5 | RFC5 | 6738 | 0.02 | 0.5 | NO
29 | POLE | POLE | POLE | 6826 | 0.018 | 0.5 | NO
30 | RPA3 | RPA3 | RPA3 | 8119 | -0.011 | 0.43 | NO
31 | RPA1 | RPA1 | RPA1 | 8295 | -0.014 | 0.42 | NO
32 | RPA2 | RPA2 | RPA2 | 8717 | -0.023 | 0.4 | NO
33 | SSBP1 | SSBP1 | SSBP1 | 10423 | -0.065 | 0.32 | NO
34 | RFC1 | RFC1 | RFC1 | 11238 | -0.086 | 0.29 | NO
35 | RPA4 | RPA4 | RPA4 | 16301 | -0.35 | 0.08 | NO

Figure S11. Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: KEGG PYRUVATE METABOLISM.

Figure S12. Get High-res Image For the top 5 core enriched genes in the pathway: KEGG PYRUVATE METABOLISM, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: KEGG RIBOSOME

Table S7. Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank | GENE | SYMBOL | DESC | LIST.LOC | S2N | RES | CORE_ENRICHMENT
--- | --- | --- | --- | --- | --- | --- | ---
1 | TP53I3 | TP53I3 | TP53I3 | 30 | 0.66 | 0.057 | YES
2 | TP73 | TP73 | TP73 | 104 | 0.55 | 0.1 | YES
3 | RRM2 | RRM2 | RRM2 | 132 | 0.52 | 0.15 | YES
4 | GTSE1 | GTSE1 | GTSE1 | 155 | 0.5 | 0.19 | YES
5 | CCNB2 | CCNB2 | CCNB2 | 298 | 0.42 | 0.22 | YES
6 | CDK1 | CDK1 | CDK1 | 365 | 0.4 | 0.25 | YES
7 | TP53AIP1 | TP53AIP1 | TP53AIP1 | 665 | 0.32 | 0.26 | YES
8 | CCNE2 | CCNE2 | CCNE2 | 779 | 0.3 | 0.28 | YES
9 | PERP | PERP | PERP | 877 | 0.29 | 0.3 | YES
10 | CHEK2 | CHEK2 | CHEK2 | 920 | 0.28 | 0.33 | YES
11 | CHEK1 | CHEK1 | CHEK1 | 959 | 0.28 | 0.35 | YES
12 | CDK6 | CDK6 | CDK6 | 1021 | 0.27 | 0.37 | YES
13 | LRDD | LRDD | LRDD | 1099 | 0.26 | 0.39 | YES
14 | SFN | SFN | SFN | 1288 | 0.23 | 0.4 | YES
15 | GADD45A | GADD45A | GADD45A | 1476 | 0.21 | 0.41 | YES
16 | CCNB1 | CCNB1 | CCNB1 | 1566 | 0.21 | 0.42 | YES
17 | CASP9 | CASP9 | CASP9 | 1585 | 0.2 | 0.44 | YES
18 | SERPINE1 | SERPINE1 | SERPINE1 | 1930 | 0.18 | 0.44 | YES
19 | TNFRSF10B | TNFRSF10B | TNFRSF10B | 2307 | 0.16 | 0.43 | YES
20 | BID | BID | BID | 2538 | 0.14 | 0.43 | YES
21 | CASP8 | CASP8 | CASP8 | 2574 | 0.14 | 0.44 | YES
22 | CASP3 | CASP3 | CASP3 | 2652 | 0.14 | 0.45 | YES
23 | CCND1 | CCND1 | CCND1 | 2782 | 0.13 | 0.45 | YES
24 | EI24 | EI24 | EI24 | 3058 | 0.12 | 0.45 | NO
25 | RFWD2 | RFWD2 | RFWD2 | 3192 | 0.12 | 0.45 | NO
26 | BAX | BAX | BAX | 3652 | 0.1 | 0.43 | NO
27 | DDB2 | DDB2 | DDB2 | 3658 | 0.1 | 0.44 | NO
28 | THBS1 | THBS1 | THBS1 | 4238 | 0.083 | 0.42 | NO
29 | CDKN2A | CDKN2A | CDKN2A | 4437 | 0.077 | 0.41 | NO
30 | SESN1 | SESN1 | SESN1 | 4734 | 0.069 | 0.4 | NO
31 | SHISA5 | SHISA5 | SHISA5 | 5140 | 0.059 | 0.38 | NO
32 | MDM4 | MDM4 | MDM4 | 5177 | 0.058 | 0.39 | NO
33 | CDK2 | CDK2 | CDK2 | 5385 | 0.053 | 0.38 | NO
34 | BBC3 | BBC3 | BBC3 | 5462 | 0.051 | 0.38 | NO
35 | SESN3 | SESN3 | SESN3 | 5883 | 0.04 | 0.36 | NO
36 | RRM2B | RRM2B | RRM2B | 6168 | 0.033 | 0.34 | NO
37 | CCNE1 | CCNE1 | CCNE1 | 6213 | 0.032 | 0.35 | NO
38 | CDKN1A | CDKN1A | CDKN1A | 6292 | 0.03 | 0.34 | NO
39 | MDM2 | MDM2 | MDM2 | 6349 | 0.029 | 0.34 | NO
40 | PTEN | PTEN | PTEN | 6877 | 0.017 | 0.32 | NO
41 | SERPINB5 | SERPINB5 | SERPINB5 | 7224 | 0.0093 | 0.3 | NO
42 | CDK4 | CDK4 | CDK4 | 7239 | 0.0089 | 0.3 | NO
43 | TP53 | TP53 | TP53 | 7338 | 0.0068 | 0.29 | NO
44 | RPRM | RPRM | RPRM | 7610 | 0.00096 | 0.28 | NO
45 | CCND3 | CCND3 | CCND3 | 8164 | -0.012 | 0.25 | NO
46 | ATM | ATM | ATM | 8503 | -0.019 | 0.23 | NO
47 | CYCS | CYCS | CYCS | 8663 | -0.022 | 0.22 | NO
48 | PPM1D | PPM1D | PPM1D | 8743 | -0.024 | 0.22 | NO
49 | IGFBP3 | IGFBP3 | IGFBP3 | 8849 | -0.026 | 0.22 | NO
50 | ATR | ATR | ATR | 9603 | -0.045 | 0.18 | NO
51 | CCNB3 | CCNB3 | CCNB3 | 10017 | -0.055 | 0.16 | NO
52 | SESN2 | SESN2 | SESN2 | 10923 | -0.078 | 0.11 | NO
53 | TSC2 | TSC2 | TSC2 | 11005 | -0.08 | 0.12 | NO
54 | CCNG1 | CCNG1 | CCNG1 | 11741 | -0.1 | 0.084 | NO
55 | FAS | FAS | FAS | 12535 | -0.12 | 0.05 | NO
56 | GADD45B | GADD45B | GADD45B | 12597 | -0.13 | 0.058 | NO
57 | BAI1 | BAI1 | BAI1 | 12947 | -0.14 | 0.05 | NO
58 | SIAH1 | SIAH1 | SIAH1 | 13595 | -0.16 | 0.028 | NO
59 | RCHY1 | RCHY1 | RCHY1 | 13686 | -0.17 | 0.038 | NO
60 | APAF1 | APAF1 | APAF1 | 14034 | -0.18 | 0.034 | NO
61 | ZMAT3 | ZMAT3 | ZMAT3 | 14728 | -0.22 | 0.015 | NO
62 | GADD45G | GADD45G | GADD45G | 14893 | -0.23 | 0.026 | NO
63 | CCND2 | CCND2 | CCND2 | 15253 | -0.25 | 0.027 | NO
64 | CCNG2 | CCNG2 | CCNG2 | 15263 | -0.25 | 0.049 | NO
65 | PMAIP1 | PMAIP1 | PMAIP1 | 15519 | -0.27 | 0.059 | NO
66 | IGF1 | IGF1 | IGF1 | 16389 | -0.36 | 0.041 | NO
67 | CD82 | CD82 | CD82 | 16538 | -0.38 | 0.067 | NO

Figure S13. Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: KEGG RIBOSOME.

Figure S14. Get High-res Image For the top 5 core enriched genes in the pathway: KEGG RIBOSOME, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: KEGG RNA DEGRADATION

Table S8. Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank | GENE | SYMBOL | DESC | LIST.LOC | S2N | RES | CORE_ENRICHMENT
--- | --- | --- | --- | --- | --- | --- | ---
1 | EXOSC8 | EXOSC8 | EXOSC8 | 1030 | 0.27 | -0.0038 | YES
2 | ENO3 | ENO3 | ENO3 | 1359 | 0.23 | 0.024 | YES
3 | RQCD1 | RQCD1 | RQCD1 | 1468 | 0.21 | 0.062 | YES
4 | HSPD1 | HSPD1 | HSPD1 | 1937 | 0.18 | 0.072 | YES
5 | DCPS | DCPS | DCPS | 1964 | 0.18 | 0.11 | YES
6 | EXOSC4 | EXOSC4 | EXOSC4 | 2570 | 0.14 | 0.1 | YES
7 | EXOSC1 | EXOSC1 | EXOSC1 | 2798 | 0.13 | 0.12 | YES
8 | EXOSC2 | EXOSC2 | EXOSC2 | 3037 | 0.12 | 0.13 | YES
9 | PATL1 | PATL1 | PATL1 | 3147 | 0.12 | 0.14 | YES
10 | EDC3 | EDC3 | EDC3 | 3229 | 0.12 | 0.16 | YES
11 | ENO1 | ENO1 | ENO1 | 3604 | 0.1 | 0.16 | YES
12 | EXOSC6 | EXOSC6 | EXOSC6 | 3683 | 0.1 | 0.18 | YES
13 | LSM2 | LSM2 | LSM2 | 3773 | 0.097 | 0.2 | YES
14 | LSM4 | LSM4 | LSM4 | 3964 | 0.091 | 0.2 | YES
15 | LSM3 | LSM3 | LSM3 | 3968 | 0.091 | 0.22 | YES
16 | LSM1 | LSM1 | LSM1 | 4077 | 0.088 | 0.23 | YES
17 | LSM7 | LSM7 | LSM7 | 4099 | 0.087 | 0.25 | YES
18 | EXOSC7 | EXOSC7 | EXOSC7 | 4167 | 0.085 | 0.26 | YES
19 | PNPT1 | PNPT1 | PNPT1 | 4237 | 0.083 | 0.28 | YES
20 | CNOT3 | CNOT3 | CNOT3 | 4406 | 0.078 | 0.28 | YES
21 | PAPOLG | PAPOLG | PAPOLG | 4539 | 0.074 | 0.29 | YES
22 | DCP2 | DCP2 | DCP2 | 4889 | 0.065 | 0.28 | NO
23 | C1D | C1D | C1D | 5109 | 0.06 | 0.28 | NO
24 | EXOSC10 | EXOSC10 | EXOSC10 | 5517 | 0.05 | 0.27 | NO
25 | EXOSC3 | EXOSC3 | EXOSC3 | 5588 | 0.047 | 0.28 | NO
26 | CNOT10 | CNOT10 | CNOT10 | 5886 | 0.039 | 0.27 | NO
27 | NAA38 | NAA38 | NAA38 | 6076 | 0.035 | 0.26 | NO
28 | EDC4 | EDC4 | EDC4 | 6352 | 0.029 | 0.26 | NO
29 | CNOT2 | CNOT2 | CNOT2 | 6457 | 0.026 | 0.25 | NO
30 | ENO2 | ENO2 | ENO2 | 7041 | 0.013 | 0.22 | NO
31 | WDR61 | WDR61 | WDR61 | 7173 | 0.01 | 0.22 | NO
32 | LSM6 | LSM6 | LSM6 | 7273 | 0.0082 | 0.22 | NO
33 | LSM5 | LSM5 | LSM5 | 7406 | 0.0051 | 0.21 | NO
34 | EXOSC9 | EXOSC9 | EXOSC9 | 7576 | 0.0017 | 0.2 | NO
35 | SKIV2L | SKIV2L | SKIV2L | 7753 | -0.0024 | 0.19 | NO
36 | DCP1A | DCP1A | DCP1A | 7847 | -0.0045 | 0.18 | NO
37 | CNOT7 | CNOT7 | CNOT7 | 7882 | -0.0053 | 0.18 | NO
38 | EXOSC5 | EXOSC5 | EXOSC5 | 7999 | -0.0077 | 0.18 | NO
39 | PAPOLA | PAPOLA | PAPOLA | 8150 | -0.011 | 0.17 | NO
40 | CNOT6L | CNOT6L | CNOT6L | 8634 | -0.022 | 0.15 | NO
41 | DIS3 | DIS3 | DIS3 | 8726 | -0.024 | 0.15 | NO
42 | CNOT1 | CNOT1 | CNOT1 | 8798 | -0.025 | 0.15 | NO
43 | DDX6 | DDX6 | DDX6 | 9368 | -0.039 | 0.13 | NO
44 | CNOT6 | CNOT6 | CNOT6 | 10018 | -0.055 | 0.1 | NO
45 | XRN1 | XRN1 | XRN1 | 10457 | -0.066 | 0.09 | NO
46 | PAPOLB | PAPOLB | PAPOLB | 10759 | -0.074 | 0.088 | NO
47 | SKIV2L2 | SKIV2L2 | SKIV2L2 | 11091 | -0.082 | 0.087 | NO
48 | PARN | PARN | PARN | 11123 | -0.083 | 0.1 | NO
49 | MPHOSPH6 | MPHOSPH6 | MPHOSPH6 | 11754 | -0.1 | 0.087 | NO
50 | ZCCHC7 | ZCCHC7 | ZCCHC7 | 12053 | -0.11 | 0.092 | NO
51 | XRN2 | XRN2 | XRN2 | 12850 | -0.13 | 0.075 | NO
52 | PAPD7 | PAPD7 | PAPD7 | 13017 | -0.14 | 0.094 | NO
53 | DCP1B | DCP1B | DCP1B | 13910 | -0.18 | 0.079 | NO
54 | HSPA9 | HSPA9 | HSPA9 | 13961 | -0.18 | 0.11 | NO
55 | CNOT4 | CNOT4 | CNOT4 | 14389 | -0.2 | 0.13 | NO
56 | TTC37 | TTC37 | TTC37 | 15769 | -0.29 | 0.11 | NO

Figure S15. Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: KEGG RNA DEGRADATION.

Figure S16. Get High-res Image For the top 5 core enriched genes in the pathway: KEGG RNA DEGRADATION, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: KEGG RNA POLYMERASE

Table S9. Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank | GENE | SYMBOL | DESC | LIST.LOC | S2N | RES | CORE_ENRICHMENT
--- | --- | --- | --- | --- | --- | --- | ---
1 | CDC25A | CDC25A | CDC25A | 109 | 0.54 | 0.18 | YES
2 | CDK1 | CDK1 | CDK1 | 365 | 0.4 | 0.3 | YES
3 | CDK6 | CDK6 | CDK6 | 1021 | 0.27 | 0.36 | YES
4 | TGFB2 | TGFB2 | TGFB2 | 1233 | 0.24 | 0.42 | YES
5 | SKP2 | SKP2 | SKP2 | 1495 | 0.21 | 0.48 | YES
6 | CCND1 | CCND1 | CCND1 | 2782 | 0.13 | 0.46 | YES
7 | SMAD3 | SMAD3 | SMAD3 | 3021 | 0.12 | 0.48 | YES
8 | DHFR | DHFR | DHFR | 4181 | 0.085 | 0.45 | YES
9 | CDKN2A | CDKN2A | CDKN2A | 4437 | 0.077 | 0.46 | YES
10 | TFDP1 | TFDP1 | TFDP1 | 4472 | 0.076 | 0.48 | YES
11 | SMAD4 | SMAD4 | SMAD4 | 4814 | 0.067 | 0.49 | YES
12 | TGFB3 | TGFB3 | TGFB3 | 5229 | 0.056 | 0.48 | YES
13 | CDK2 | CDK2 | CDK2 | 5385 | 0.053 | 0.49 | YES
14 | CCNE1 | CCNE1 | CCNE1 | 6213 | 0.032 | 0.46 | NO
15 | CDKN1A | CDKN1A | CDKN1A | 6292 | 0.03 | 0.46 | NO
16 | TGFB1 | TGFB1 | TGFB1 | 6567 | 0.024 | 0.46 | NO
17 | CDK4 | CDK4 | CDK4 | 7239 | 0.0089 | 0.42 | NO
18 | TP53 | TP53 | TP53 | 7338 | 0.0068 | 0.42 | NO
19 | HDAC1 | HDAC1 | HDAC1 | 7532 | 0.0027 | 0.41 | NO
20 | GSK3B | GSK3B | GSK3B | 8169 | -0.012 | 0.38 | NO
21 | ATM | ATM | ATM | 8503 | -0.019 | 0.36 | NO
22 | ABL1 | ABL1 | ABL1 | 8542 | -0.02 | 0.37 | NO
23 | CCNA1 | CCNA1 | CCNA1 | 9427 | -0.041 | 0.33 | NO
24 | ATR | ATR | ATR | 9603 | -0.045 | 0.34 | NO
25 | CDKN1B | CDKN1B | CDKN1B | 10878 | -0.077 | 0.29 | NO
26 | RB1 | RB1 | RB1 | 12214 | -0.11 | 0.26 | NO
27 | CDKN2B | CDKN2B | CDKN2B | 13643 | -0.16 | 0.23 | NO

Figure S17. Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: KEGG RNA POLYMERASE.

Figure S18. Get High-res Image For the top 5 core enriched genes in the pathway: KEGG RNA POLYMERASE, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: KEGG DNA REPLICATION

Table S10. Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank | GENE | SYMBOL | DESC | LIST.LOC | S2N | RES | CORE_ENRICHMENT
--- | --- | --- | --- | --- | --- | --- | ---
1 | CDK1 | CDK1 | CDK1 | 365 | 0.4 | 0.071 | YES
2 | CDC25C | CDC25C | CDC25C | 751 | 0.31 | 0.12 | YES
3 | RPS6KA1 | RPS6KA1 | RPS6KA1 | 1114 | 0.25 | 0.16 | YES
4 | HRAS | HRAS | HRAS | 1160 | 0.25 | 0.21 | YES
5 | ACTA1 | ACTA1 | ACTA1 | 1456 | 0.22 | 0.24 | YES
6 | ARPC2 | ARPC2 | ARPC2 | 1561 | 0.21 | 0.28 | YES
7 | CCNB1 | CCNB1 | CCNB1 | 1566 | 0.21 | 0.33 | YES
8 | ACTR3 | ACTR3 | ACTR3 | 2128 | 0.17 | 0.34 | YES
9 | PAQR7 | PAQR7 | PAQR7 | 2301 | 0.16 | 0.36 | YES
10 | ARPC1B | ARPC1B | ARPC1B | 2607 | 0.14 | 0.38 | YES
11 | PAQR5 | PAQR5 | PAQR5 | 2725 | 0.14 | 0.4 | YES
12 | ARPC5 | ARPC5 | ARPC5 | 3068 | 0.12 | 0.41 | YES
13 | ARPC4 | ARPC4 | ARPC4 | 3282 | 0.11 | 0.42 | YES
14 | ACTR2 | ACTR2 | ACTR2 | 4403 | 0.079 | 0.38 | NO
15 | PRKAR2B | PRKAR2B | PRKAR2B | 5300 | 0.055 | 0.34 | NO
16 | PIN1 | PIN1 | PIN1 | 5393 | 0.053 | 0.35 | NO
17 | MAPK1 | MAPK1 | MAPK1 | 5704 | 0.044 | 0.34 | NO
18 | GNB1 | GNB1 | GNB1 | 5711 | 0.044 | 0.35 | NO
19 | ARPC1A | ARPC1A | ARPC1A | 8519 | -0.019 | 0.2 | NO
20 | CAP1 | CAP1 | CAP1 | 8864 | -0.027 | 0.18 | NO
21 | PRKAR1B | PRKAR1B | PRKAR1B | 8969 | -0.029 | 0.18 | NO
22 | ARPC3 | ARPC3 | ARPC3 | 10140 | -0.058 | 0.13 | NO
23 | PRKACB | PRKACB | PRKACB | 10493 | -0.067 | 0.13 | NO
24 | MAPK3 | MAPK3 | MAPK3 | 10570 | -0.069 | 0.14 | NO
25 | GNAS | GNAS | GNAS | 10723 | -0.073 | 0.15 | NO
26 | PRKAR1A | PRKAR1A | PRKAR1A | 10768 | -0.074 | 0.16 | NO
27 | PRKAR2A | PRKAR2A | PRKAR2A | 10996 | -0.08 | 0.17 | NO
28 | PGR | PGR | PGR | 11313 | -0.088 | 0.17 | NO
29 | SRC | SRC | SRC | 13200 | -0.15 | 0.095 | NO
30 | GNAI1 | GNAI1 | GNAI1 | 13465 | -0.16 | 0.12 | NO
31 | MYT1 | MYT1 | MYT1 | 15487 | -0.27 | 0.062 | NO
32 | PRKACG | PRKACG | PRKACG | 15671 | -0.28 | 0.12 | NO

Figure S19. Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: KEGG DNA REPLICATION.

Figure S20. Get High-res Image For the top 5 core enriched genes in the pathway: KEGG DNA REPLICATION, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

Fold change

For the top enriched genes, if you want to check whether they are

- up-regulated, please check the list of up-regulated genes

- down-regulated, please check the list of down-regulated genes

Expression level

For the top enriched genes, if you want to check whether they are

- highly expressed genes, please check the list of high (top 30%) expressed genes

- low expressed genes, please check the list of low (bottom 30%) expressed genes

An expression pattern of top(30%)/middle(30%)/low(30%) in this subtype against other subtypes is available in a heatmap

Significant gene list

For the top enriched genes, if you want to check whether they are

- significantly differently expressed genes by eBayes lm fit, please check the list of significant genes

Subtype clus2 enriched pathways

Table 4. Get Full Table This table shows top 10 pathways which are significantly enriched in cluster clus2. It displays only significant gene sets satisfying nom.p.val.threshold (-1), fwer.p.val.threshold (-1) , fdr.q.val.threshold (0.25) and the default table is sorted by Normalized Enrichment Score (NES). Further details on NES statistics, please visit The Broad GSEA website.

GeneSet(GS) | Size(#genes) | genes.ES.table | ES | NES | NOM.p.val | FDR.q.val | FWER.p.val | Tag.. | Gene.. | Signal | FDR..median. | glob.p.val
--- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | ---
BIOCARTA NO1 PATHWAY | 27 | genes.ES.table | 0.59 | 1.6 | 0.024 | 0.8 | 0.65 | 0.33 | 0.15 | 0.28 | 0.48 | 0.29
BIOCARTA AGR PATHWAY | 33 | genes.ES.table | 0.39 | 1.3 | 0.16 | 0.68 | 0.99 | 0.24 | 0.12 | 0.21 | 0.6 | 0.19
BIOCARTA ALK PATHWAY | 34 | genes.ES.table | 0.52 | 1.5 | 0.028 | 0.8 | 0.81 | 0.29 | 0.21 | 0.23 | 0.56 | 0.29
BIOCARTA VIP PATHWAY | 25 | genes.ES.table | 0.48 | 1.4 | 0.13 | 0.65 | 0.95 | 0.44 | 0.33 | 0.3 | 0.52 | 0.19
BIOCARTA CHREBP2 PATHWAY | 41 | genes.ES.table | 0.38 | 1.3 | 0.16 | 0.63 | 0.98 | 0.12 | 0.091 | 0.11 | 0.55 | 0.16
BIOCARTA WNT PATHWAY | 25 | genes.ES.table | 0.52 | 1.8 | 0.013 | 0.53 | 0.34 | 0.6 | 0.38 | 0.37 | 0 | 0.19
KEGG CYSTEINE AND METHIONINE METABOLISM | 32 | genes.ES.table | 0.43 | 1.4 | 0.08 | 0.65 | 0.94 | 0.16 | 0.1 | 0.14 | 0.51 | 0.2
KEGG GLYCOSAMINOGLYCAN BIOSYNTHESIS HEPARAN SULFATE | 25 | genes.ES.table | 0.46 | 1.3 | 0.16 | 0.61 | 0.98 | 0.2 | 0.13 | 0.18 | 0.53 | 0.15
KEGG MAPK SIGNALING PATHWAY | 246 | genes.ES.table | 0.34 | 1.3 | 0.064 | 0.66 | 0.97 | 0.22 | 0.16 | 0.19 | 0.56 | 0.18
KEGG WNT SIGNALING PATHWAY | 144 | genes.ES.table | 0.39 | 1.5 | 0.038 | 0.84 | 0.91 | 0.33 | 0.22 | 0.26 | 0.64 | 0.31

genes ES table in pathway: BIOCARTA NO1 PATHWAY

Table S11. Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank | GENE | SYMBOL | DESC | LIST.LOC | S2N | RES | CORE_ENRICHMENT
--- | --- | --- | --- | --- | --- | --- | ---
1 | WIF1 | WIF1 | WIF1 | 204 | 0.57 | 0.19 | YES
2 | LEF1 | LEF1 | LEF1 | 218 | 0.57 | 0.39 | YES
3 | TLE1 | TLE1 | TLE1 | 2162 | 0.22 | 0.35 | YES
4 | MYC | MYC | MYC | 2845 | 0.18 | 0.38 | YES
5 | CTNNB1 | CTNNB1 | CTNNB1 | 3473 | 0.15 | 0.4 | YES
6 | CCND1 | CCND1 | CCND1 | 3579 | 0.14 | 0.44 | YES
7 | FRAT1 | FRAT1 | FRAT1 | 4165 | 0.12 | 0.45 | YES
8 | BTRC | BTRC | BTRC | 4421 | 0.11 | 0.48 | YES
9 | APC | APC | APC | 5010 | 0.097 | 0.48 | YES
10 | GSK3B | GSK3B | GSK3B | 5332 | 0.088 | 0.49 | YES
11 | FZD1 | FZD1 | FZD1 | 5728 | 0.078 | 0.49 | YES
12 | CSNK1A1 | CSNK1A1 | CSNK1A1 | 5853 | 0.075 | 0.51 | YES
13 | WNT1 | WNT1 | WNT1 | 6283 | 0.066 | 0.51 | YES
14 | NLK | NLK | NLK | 6569 | 0.059 | 0.52 | YES
15 | CREBBP | CREBBP | CREBBP | 6766 | 0.055 | 0.52 | YES
16 | CSNK2A1 | CSNK2A1 | CSNK2A1 | 8245 | 0.026 | 0.45 | NO
17 | AXIN1 | AXIN1 | AXIN1 | 8325 | 0.025 | 0.45 | NO
18 | MAP3K7 | MAP3K7 | MAP3K7 | 9085 | 0.011 | 0.41 | NO
19 | PPP2CA | PPP2CA | PPP2CA | 9144 | 0.0098 | 0.41 | NO
20 | CSNK1D | CSNK1D | CSNK1D | 9591 | 0.0015 | 0.39 | NO
21 | CTBP1 | CTBP1 | CTBP1 | 10485 | -0.016 | 0.34 | NO
22 | SMAD4 | SMAD4 | SMAD4 | 10531 | -0.017 | 0.35 | NO
23 | DVL1 | DVL1 | DVL1 | 11135 | -0.028 | 0.32 | NO
24 | TAB1 | TAB1 | TAB1 | 11317 | -0.032 | 0.32 | NO
25 | HDAC1 | HDAC1 | HDAC1 | 14183 | -0.11 | 0.2 | NO

Figure S21. Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: BIOCARTA NO1 PATHWAY.

Figure S22. Get High-res Image For the top 5 core enriched genes in the pathway: BIOCARTA NO1 PATHWAY, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: BIOCARTA AGR PATHWAY

Table S12. Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank | GENE | SYMBOL | DESC | LIST.LOC | S2N | RES | CORE_ENRICHMENT
--- | --- | --- | --- | --- | --- | --- | ---
1 | PDE2A | PDE2A | PDE2A | 54 | 0.73 | 0.18 | YES
2 | RYR2 | RYR2 | RYR2 | 589 | 0.42 | 0.26 | YES
3 | SLC7A1 | SLC7A1 | SLC7A1 | 1092 | 0.33 | 0.31 | YES
4 | PRKAR1B | PRKAR1B | PRKAR1B | 1343 | 0.3 | 0.37 | YES
5 | PDE3A | PDE3A | PDE3A | 1533 | 0.28 | 0.43 | YES
6 | PRKAR2B | PRKAR2B | PRKAR2B | 1609 | 0.27 | 0.5 | YES
7 | PRKG1 | PRKG1 | PRKG1 | 1808 | 0.25 | 0.55 | YES
8 | PDE3B | PDE3B | PDE3B | 2652 | 0.19 | 0.55 | YES
9 | PRKAR2A | PRKAR2A | PRKAR2A | 2689 | 0.19 | 0.59 | YES
10 | FLT1 | FLT1 | FLT1 | 5329 | 0.088 | 0.46 | NO
11 | PRKACG | PRKACG | PRKACG | 5438 | 0.085 | 0.48 | NO
12 | VEGFA | VEGFA | VEGFA | 5499 | 0.084 | 0.5 | NO
13 | CALM1 | CALM1 | CALM1 | 7458 | 0.042 | 0.4 | NO
14 | CALM3 | CALM3 | CALM3 | 8416 | 0.023 | 0.35 | NO
15 | AKT1 | AKT1 | AKT1 | 8859 | 0.015 | 0.33 | NO
16 | CALM2 | CALM2 | CALM2 | 8948 | 0.014 | 0.33 | NO
17 | PRKAR1A | PRKAR1A | PRKAR1A | 9822 | -0.0028 | 0.28 | NO
18 | HSP90AA1 | HSP90AA1 | HSP90AA1 | 10070 | -0.0077 | 0.26 | NO
19 | PRKACB | PRKACB | PRKACB | 10326 | -0.012 | 0.25 | NO
20 | KNG1 | KNG1 | KNG1 | 10603 | -0.018 | 0.24 | NO
21 | KDR | KDR | KDR | 10775 | -0.021 | 0.24 | NO
22 | NOS3 | NOS3 | NOS3 | 12342 | -0.054 | 0.16 | NO
23 | FLT4 | FLT4 | FLT4 | 12359 | -0.055 | 0.18 | NO
24 | PRKG2 | PRKG2 | PRKG2 | 13074 | -0.072 | 0.15 | NO
25 | ACTA1 | ACTA1 | ACTA1 | 14350 | -0.11 | 0.11 | NO
26 | BDKRB2 | BDKRB2 | BDKRB2 | 14719 | -0.13 | 0.12 | NO
27 | CHRNA1 | CHRNA1 | CHRNA1 | 15744 | -0.19 | 0.11 | NO

Figure S23. Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: BIOCARTA AGR PATHWAY.

Figure S24. Get High-res Image For the top 5 core enriched genes in the pathway: BIOCARTA AGR PATHWAY, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: BIOCARTA ALK PATHWAY

Table S13. Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank | GENE | SYMBOL | DESC | LIST.LOC | S2N | RES | CORE_ENRICHMENT
--- | --- | --- | --- | --- | --- | --- | ---
1 | WNT4 | WNT4 | WNT4 | 108 | 0.65 | 0.055 | YES
2 | LEF1 | LEF1 | LEF1 | 218 | 0.57 | 0.1 | YES
3 | AXIN2 | AXIN2 | AXIN2 | 350 | 0.5 | 0.14 | YES
4 | GLI1 | GLI1 | GLI1 | 368 | 0.49 | 0.19 | YES
5 | SHH | SHH | SHH | 487 | 0.46 | 0.22 | YES
6 | BMP4 | BMP4 | BMP4 | 556 | 0.43 | 0.26 | YES
7 | SMO | SMO | SMO | 656 | 0.41 | 0.29 | YES
8 | WNT9A | WNT9A | WNT9A | 1076 | 0.34 | 0.3 | YES
9 | TCF7 | TCF7 | TCF7 | 1094 | 0.33 | 0.33 | YES
10 | FZD10 | FZD10 | FZD10 | 1125 | 0.33 | 0.36 | YES
11 | WNT10B | WNT10B | WNT10B | 1336 | 0.3 | 0.38 | YES
12 | FZD7 | FZD7 | FZD7 | 1362 | 0.3 | 0.4 | YES
13 | FZD6 | FZD6 | FZD6 | 1551 | 0.28 | 0.42 | YES
14 | PTCH2 | PTCH2 | PTCH2 | 1585 | 0.28 | 0.44 | YES
15 | FZD9 | FZD9 | FZD9 | 1621 | 0.27 | 0.46 | YES
16 | GLI3 | GLI3 | GLI3 | 1651 | 0.27 | 0.49 | YES
17 | HHIP | HHIP | HHIP | 2052 | 0.23 | 0.49 | YES
18 | APC2 | APC2 | APC2 | 2133 | 0.23 | 0.5 | YES
19 | PTCH1 | PTCH1 | PTCH1 | 2185 | 0.22 | 0.52 | YES
20 | WNT5A | WNT5A | WNT5A | 2446 | 0.2 | 0.52 | YES
21 | FZD8 | FZD8 | FZD8 | 2592 | 0.2 | 0.54 | YES
22 | WNT3 | WNT3 | WNT3 | 2981 | 0.17 | 0.53 | YES
23 | TCF7L2 | TCF7L2 | TCF7L2 | 3024 | 0.17 | 0.54 | YES
24 | WNT16 | WNT16 | WNT16 | 3241 | 0.16 | 0.55 | YES
25 | WNT2 | WNT2 | WNT2 | 3359 | 0.15 | 0.55 | YES
26 | CTNNB1 | CTNNB1 | CTNNB1 | 3473 | 0.15 | 0.56 | YES
27 | GLI2 | GLI2 | GLI2 | 4049 | 0.13 | 0.54 | NO
28 | TCF7L1 | TCF7L1 | TCF7L1 | 4210 | 0.12 | 0.54 | NO
29 | WNT6 | WNT6 | WNT6 | 4856 | 0.1 | 0.52 | NO
30 | APC | APC | APC | 5010 | 0.097 | 0.52 | NO
31 | SUFU | SUFU | SUFU | 5171 | 0.092 | 0.52 | NO
32 | GSK3B | GSK3B | GSK3B | 5332 | 0.088 | 0.52 | NO
33 | TP53 | TP53 | TP53 | 5427 | 0.086 | 0.52 | NO
34 | FZD3 | FZD3 | FZD3 | 5537 | 0.082 | 0.52 | NO
35 | WNT11 | WNT11 | WNT11 | 5672 | 0.08 | 0.52 | NO
36 | FZD1 | FZD1 | FZD1 | 5728 | 0.078 | 0.52 | NO
37 | DVL3 | DVL3 | DVL3 | 5971 | 0.073 | 0.52 | NO
38 | WNT1 | WNT1 | WNT1 | 6283 | 0.066 | 0.5 | NO
39 | WNT7B | WNT7B | WNT7B | 6321 | 0.065 | 0.51 | NO
40 | BMP2 | BMP2 | BMP2 | 6924 | 0.052 | 0.48 | NO
41 | FZD5 | FZD5 | FZD5 | 7375 | 0.043 | 0.46 | NO
42 | AXIN1 | AXIN1 | AXIN1 | 8325 | 0.025 | 0.41 | NO
43 | WNT8B | WNT8B | WNT8B | 9877 | -0.004 | 0.32 | NO
44 | DVL1 | DVL1 | DVL1 | 11135 | -0.028 | 0.25 | NO
45 | DVL2 | DVL2 | DVL2 | 12119 | -0.049 | 0.2 | NO
46 | WNT10A | WNT10A | WNT10A | 12752 | -0.064 | 0.17 | NO
47 | STK36 | STK36 | STK36 | 12829 | -0.066 | 0.17 | NO
48 | FZD2 | FZD2 | FZD2 | 12974 | -0.07 | 0.17 | NO
49 | FZD4 | FZD4 | FZD4 | 13521 | -0.086 | 0.15 | NO
50 | WNT2B | WNT2B | WNT2B | 14533 | -0.12 | 0.1 | NO
51 | WNT9B | WNT9B | WNT9B | 15392 | -0.17 | 0.068 | NO
52 | WNT7A | WNT7A | WNT7A | 15580 | -0.18 | 0.074 | NO
53 | WNT5B | WNT5B | WNT5B | 17580 | -0.5 | 0.0078 | NO

Figure S25. Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: BIOCARTA ALK PATHWAY.

Figure S26. Get High-res Image For the top 5 core enriched genes in the pathway: BIOCARTA ALK PATHWAY, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: BIOCARTA VIP PATHWAY

Table S14. Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank | GENE | SYMBOL | DESC | LIST.LOC | S2N | RES | CORE_ENRICHMENT
--- | --- | --- | --- | --- | --- | --- | ---
1 | CHRD | CHRD | CHRD | 144 | 0.62 | 0.13 | YES
2 | TGFB2 | TGFB2 | TGFB2 | 299 | 0.52 | 0.24 | YES
3 | NOG | NOG | NOG | 395 | 0.48 | 0.34 | YES
4 | BMP4 | BMP4 | BMP4 | 556 | 0.43 | 0.42 | YES
5 | BMP7 | BMP7 | BMP7 | 1029 | 0.34 | 0.47 | YES
6 | NKX2-5 | NKX2-5 | NKX2-5 | 1873 | 0.25 | 0.48 | YES
7 | TGFB3 | TGFB3 | TGFB3 | 2437 | 0.2 | 0.5 | YES
8 | CTNNB1 | CTNNB1 | CTNNB1 | 3473 | 0.15 | 0.47 | YES
9 | RFC1 | RFC1 | RFC1 | 3656 | 0.14 | 0.49 | YES
10 | SMAD5 | SMAD5 | SMAD5 | 3710 | 0.14 | 0.52 | YES
11 | SMAD1 | SMAD1 | SMAD1 | 4907 | 0.1 | 0.47 | NO
12 | APC | APC | APC | 5010 | 0.097 | 0.49 | NO
13 | GSK3B | GSK3B | GSK3B | 5332 | 0.088 | 0.49 | NO
14 | FZD1 | FZD1 | FZD1 | 5728 | 0.078 | 0.48 | NO
15 | ATF2 | ATF2 | ATF2 | 5739 | 0.078 | 0.5 | NO
16 | BMPR1A | BMPR1A | BMPR1A | 5987 | 0.072 | 0.5 | NO
17 | WNT1 | WNT1 | WNT1 | 6283 | 0.066 | 0.5 | NO
18 | BMP2 | BMP2 | BMP2 | 6924 | 0.052 | 0.48 | NO
19 | HNF1A | HNF1A | HNF1A | 7956 | 0.032 | 0.43 | NO
20 | GATA4 | GATA4 | GATA4 | 7959 | 0.032 | 0.43 | NO
21 | BMPR2 | BMPR2 | BMPR2 | 7999 | 0.031 | 0.44 | NO
22 | AXIN1 | AXIN1 | AXIN1 | 8325 | 0.025 | 0.42 | NO
23 | NPPB | NPPB | NPPB | 8726 | 0.018 | 0.41 | NO
24 | MAP3K7 | MAP3K7 | MAP3K7 | 9085 | 0.011 | 0.39 | NO
25 | TGFBR2 | TGFBR2 | TGFBR2 | 9502 | 0.003 | 0.36 | NO
26 | SMAD6 | SMAD6 | SMAD6 | 9791 | -0.0024 | 0.35 | NO
27 | SMAD4 | SMAD4 | SMAD4 | 10531 | -0.017 | 0.31 | NO
28 | MYL2 | MYL2 | MYL2 | 10625 | -0.019 | 0.31 | NO
29 | TGFBR1 | TGFBR1 | TGFBR1 | 10908 | -0.024 | 0.3 | NO
30 | TGFBR3 | TGFBR3 | TGFBR3 | 11034 | -0.026 | 0.3 | NO
31 | DVL1 | DVL1 | DVL1 | 11135 | -0.028 | 0.3 | NO
32 | TGFB1 | TGFB1 | TGFB1 | 12082 | -0.048 | 0.26 | NO
33 | ACVR1 | ACVR1 | ACVR1 | 13232 | -0.077 | 0.21 | NO
34 | NPPA | NPPA | NPPA | 15905 | -0.21 | 0.1 | NO

Figure S27. Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: BIOCARTA VIP PATHWAY.

Figure S28. Get High-res Image For the top 5 core enriched genes in the pathway: BIOCARTA VIP PATHWAY, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: BIOCARTA CHREBP2 PATHWAY

Table S15. Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank | GENE | SYMBOL | DESC | LIST.LOC | S2N | RES | CORE_ENRICHMENT
--- | --- | --- | --- | --- | --- | --- | ---
1 | TAS2R31 | TAS2R31 | TAS2R31 | 48 | 0.76 | 0.076 | YES
2 | CACNA1B | CACNA1B | CACNA1B | 84 | 0.67 | 0.14 | YES
3 | TAS2R14 | TAS2R14 | TAS2R14 | 97 | 0.66 | 0.21 | YES
4 | TAS2R46 | TAS2R46 | TAS2R46 | 327 | 0.51 | 0.25 | YES
5 | TAS2R43 | TAS2R43 | TAS2R43 | 349 | 0.5 | 0.3 | YES
6 | KCNB1 | KCNB1 | KCNB1 | 408 | 0.48 | 0.35 | YES
7 | TAS2R10 | TAS2R10 | TAS2R10 | 431 | 0.47 | 0.4 | YES
8 | GNB3 | GNB3 | GNB3 | 535 | 0.44 | 0.44 | YES
9 | TAS2R19 | TAS2R19 | TAS2R19 | 536 | 0.44 | 0.48 | YES
10 | TAS2R13 | TAS2R13 | TAS2R13 | 660 | 0.41 | 0.52 | YES
11 | TAS2R42 | TAS2R42 | TAS2R42 | 757 | 0.39 | 0.55 | YES
12 | TAS2R20 | TAS2R20 | TAS2R20 | 1469 | 0.28 | 0.54 | YES
13 | TAS2R50 | TAS2R50 | TAS2R50 | 1696 | 0.26 | 0.56 | YES
14 | CACNA1A | CACNA1A | CACNA1A | 2413 | 0.21 | 0.54 | YES
15 | TAS2R5 | TAS2R5 | TAS2R5 | 2414 | 0.21 | 0.56 | YES
16 | PRKX | PRKX | PRKX | 2544 | 0.2 | 0.57 | YES
17 | ADCY6 | ADCY6 | ADCY6 | 3791 | 0.14 | 0.52 | NO
18 | PRKACG | PRKACG | PRKACG | 5438 | 0.085 | 0.43 | NO
19 | ACCN1 | ACCN1 | ACCN1 | 6660 | 0.057 | 0.37 | NO
20 | PRKACA | PRKACA | PRKACA | 6667 | 0.057 | 0.38 | NO
21 | ADCY8 | ADCY8 | ADCY8 | 7530 | 0.04 | 0.33 | NO
22 | SCNN1B | SCNN1B | SCNN1B | 7545 | 0.04 | 0.33 | NO
23 | GRM4 | GRM4 | GRM4 | 8667 | 0.019 | 0.27 | NO
24 | SCNN1G | SCNN1G | SCNN1G | 9447 | 0.0039 | 0.23 | NO
25 | PRKACB | PRKACB | PRKACB | 10326 | -0.012 | 0.18 | NO
26 | TAS1R1 | TAS1R1 | TAS1R1 | 11260 | -0.03 | 0.13 | NO
27 | TAS2R4 | TAS2R4 | TAS2R4 | 11995 | -0.046 | 0.094 | NO
28 | TRPM5 | TRPM5 | TRPM5 | 12459 | -0.057 | 0.074 | NO
29 | GNAS | GNAS | GNAS | 12830 | -0.066 | 0.06 | NO
30 | GNB1 | GNB1 | GNB1 | 13288 | -0.078 | 0.042 | NO
31 | PDE1A | PDE1A | PDE1A | 14985 | -0.14 | -0.039 | NO
32 | TAS1R3 | TAS1R3 | TAS1R3 | 15936 | -0.21 | -0.072 | NO
33 | GNG3 | GNG3 | GNG3 | 15955 | -0.21 | -0.05 | NO
34 | SCNN1A | SCNN1A | SCNN1A | 15970 | -0.21 | -0.029 | NO
35 | ADCY4 | ADCY4 | ADCY4 | 16192 | -0.24 | -0.017 | NO
36 | PLCB2 | PLCB2 | PLCB2 | 16947 | -0.32 | -0.026 | NO
37 | ITPR3 | ITPR3 | ITPR3 | 17695 | -0.67 | 0.0012 | NO

Figure S29. Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: BIOCARTA CHREBP2 PATHWAY.

Figure S30. Get High-res Image For the top 5 core enriched genes in the pathway: BIOCARTA CHREBP2 PATHWAY, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: BIOCARTA WNT PATHWAY

Table S16. Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank | GENE | SYMBOL | DESC | LIST.LOC | S2N | RES | CORE_ENRICHMENT
--- | --- | --- | --- | --- | --- | --- | ---
1 | NKD1 | NKD1 | NKD1 | 52 | 0.74 | 0.03 | YES
2 | WNT4 | WNT4 | WNT4 | 108 | 0.65 | 0.056 | YES
3 | NFATC4 | NFATC4 | NFATC4 | 180 | 0.59 | 0.079 | YES
4 | WIF1 | WIF1 | WIF1 | 204 | 0.57 | 0.1 | YES
5 | LEF1 | LEF1 | LEF1 | 218 | 0.57 | 0.13 | YES
6 | PRICKLE1 | PRICKLE1 | PRICKLE1 | 246 | 0.55 | 0.15 | YES
7 | AXIN2 | AXIN2 | AXIN2 | 350 | 0.5 | 0.17 | YES
8 | VANGL2 | VANGL2 | VANGL2 | 549 | 0.44 | 0.18 | YES
9 | CAMK2B | CAMK2B | CAMK2B | 573 | 0.43 | 0.19 | YES
10 | CSNK1A1L | CSNK1A1L | CSNK1A1L | 750 | 0.39 | 0.2 | YES
11 | SFRP5 | SFRP5 | SFRP5 | 859 | 0.37 | 0.21 | YES
12 | NFATC2 | NFATC2 | NFATC2 | 869 | 0.37 | 0.23 | YES
13 | PRKCG | PRKCG | PRKCG | 1002 | 0.35 | 0.24 | YES
14 | WNT9A | WNT9A | WNT9A | 1076 | 0.34 | 0.25 | YES
15 | TCF7 | TCF7 | TCF7 | 1094 | 0.33 | 0.26 | YES
16 | FZD10 | FZD10 | FZD10 | 1125 | 0.33 | 0.27 | YES
17 | SFRP4 | SFRP4 | SFRP4 | 1322 | 0.3 | 0.28 | YES
18 | WNT10B | WNT10B | WNT10B | 1336 | 0.3 | 0.29 | YES
19 | FZD7 | FZD7 | FZD7 | 1362 | 0.3 | 0.3 | YES
20 | MAPK8 | MAPK8 | MAPK8 | 1399 | 0.29 | 0.31 | YES
21 | FZD6 | FZD6 | FZD6 | 1551 | 0.28 | 0.32 | YES
22 | FZD9 | FZD9 | FZD9 | 1621 | 0.27 | 0.32 | YES
23 | TBL1X | TBL1X | TBL1X | 1980 | 0.24 | 0.31 | YES
24 | APC2 | APC2 | APC2 | 2133 | 0.23 | 0.32 | YES
25 | LRP5 | LRP5 | LRP5 | 2209 | 0.22 | 0.32 | YES
26 | WNT5A | WNT5A | WNT5A | 2446 | 0.2 | 0.32 | YES
27 | CXXC4 | CXXC4 | CXXC4 | 2458 | 0.2 | 0.33 | YES
28 | PRKX | PRKX | PRKX | 2544 | 0.2 | 0.33 | YES
29 | FZD8 | FZD8 | FZD8 | 2592 | 0.2 | 0.34 | YES
30 | PLCB4 | PLCB4 | PLCB4 | 2619 | 0.19 | 0.34 | YES
31 | MYC | MYC | MYC | 2845 | 0.18 | 0.34 | YES
32 | WNT3 | WNT3 | WNT3 | 2981 | 0.17 | 0.34 | YES
33 | CTBP2 | CTBP2 | CTBP2 | 2998 | 0.17 | 0.34 | YES
34 | TCF7L2 | TCF7L2 | TCF7L2 | 3024 | 0.17 | 0.35 | YES
35 | CAMK2G | CAMK2G | CAMK2G | 3053 | 0.17 | 0.36 | YES
36 | SFRP1 | SFRP1 | SFRP1 | 3163 | 0.16 | 0.36 | YES
37 | PPP2R5E | PPP2R5E | PPP2R5E | 3210 | 0.16 | 0.36 | YES
38 | WNT16 | WNT16 | WNT16 | 3241 | 0.16 | 0.37 | YES
39 | PLCB1 | PLCB1 | PLCB1 | 3301 | 0.16 | 0.37 | YES
40 | WNT2 | WNT2 | WNT2 | 3359 | 0.15 | 0.38 | YES
41 | CTNNB1 | CTNNB1 | CTNNB1 | 3473 | 0.15 | 0.38 | YES
42 | CCND1 | CCND1 | CCND1 | 3579 | 0.14 | 0.38 | YES
43 | LRP6 | LRP6 | LRP6 | 3602 | 0.14 | 0.38 | YES
44 | NKD2 | NKD2 | NKD2 | 3704 | 0.14 | 0.38 | YES
45 | FBXW11 | FBXW11 | FBXW11 | 3752 | 0.14 | 0.39 | YES
46 | FRAT2 | FRAT2 | FRAT2 | 3766 | 0.14 | 0.39 | YES
47 | DAAM2 | DAAM2 | DAAM2 | 3845 | 0.13 | 0.39 | YES
48 | DAAM1 | DAAM1 | DAAM1 | 4159 | 0.12 | 0.38 | NO
49 | FRAT1 | FRAT1 | FRAT1 | 4165 | 0.12 | 0.38 | NO
50 | TCF7L1 | TCF7L1 | TCF7L1 | 4210 | 0.12 | 0.39 | NO
51 | NFATC1 | NFATC1 | NFATC1 | 4384 | 0.12 | 0.38 | NO
52 | BTRC | BTRC | BTRC | 4421 | 0.11 | 0.39 | NO
53 | NFAT5 | NFAT5 | NFAT5 | 4595 | 0.11 | 0.38 | NO
54 | SMAD3 | SMAD3 | SMAD3 | 4734 | 0.1 | 0.38 | NO
55 | MAPK10 | MAPK10 | MAPK10 | 4794 | 0.1 | 0.38 | NO
56 | WNT6 | WNT6 | WNT6 | 4856 | 0.1 | 0.38 | NO
57 | PPP3R1 | PPP3R1 | PPP3R1 | 4903 | 0.1 | 0.38 | NO
58 | PPP3CA | PPP3CA | PPP3CA | 4977 | 0.098 | 0.38 | NO
59 | APC | APC | APC | 5010 | 0.097 | 0.39 | NO
60 | PPP3CB | PPP3CB | PPP3CB | 5186 | 0.092 | 0.38 | NO
61 | GSK3B | GSK3B | GSK3B | 5332 | 0.088 | 0.38 | NO
62 | TBL1XR1 | TBL1XR1 | TBL1XR1 | 5351 | 0.088 | 0.38 | NO
63 | SKP1 | SKP1 | SKP1 | 5414 | 0.086 | 0.38 | NO
64 | TP53 | TP53 | TP53 | 5427 | 0.086 | 0.38 | NO
65 | PRKACG | PRKACG | PRKACG | 5438 | 0.085 | 0.38 | NO
66 | FZD3 | FZD3 | FZD3 | 5537 | 0.082 | 0.38 | NO
67 | WNT11 | WNT11 | WNT11 | 5672 | 0.08 | 0.38 | NO
68 | CCND2 | CCND2 | CCND2 | 5680 | 0.079 | 0.38 | NO
69 | PPP2R5C | PPP2R5C | PPP2R5C | 5696 | 0.079 | 0.38 | NO
70 | FZD1 | FZD1 | FZD1 | 5728 | 0.078 | 0.39 | NO
71 | CUL1 | CUL1 | CUL1 | 5820 | 0.076 | 0.38 | NO
72 | CSNK1A1 | CSNK1A1 | CSNK1A1 | 5853 | 0.075 | 0.39 | NO
73 | DVL3 | DVL3 | DVL3 | 5971 | 0.073 | 0.38 | NO
74 | EP300 | EP300 | EP300 | 5989 | 0.072 | 0.38 | NO
75 | PRICKLE2 | PRICKLE2 | PRICKLE2 | 6142 | 0.069 | 0.38 | NO
76 | CHD8 | CHD8 | CHD8 | 6162 | 0.069 | 0.38 | NO
77 | WNT1 | WNT1 | WNT1 | 6283 | 0.066 | 0.38 | NO
78 | WNT7B | WNT7B | WNT7B | 6321 | 0.065 | 0.38 | NO
79 | SENP2 | SENP2 | SENP2 | 6374 | 0.064 | 0.38 | NO
80 | NLK | NLK | NLK | 6569 | 0.059 | 0.37 | NO
81 | PRKACA | PRKACA | PRKACA | 6667 | 0.057 | 0.37 | NO
82 | SMAD2 | SMAD2 | SMAD2 | 6705 | 0.056 | 0.37 | NO
83 | CSNK1E | CSNK1E | CSNK1E | 6707 | 0.056 | 0.37 | NO
84 | CREBBP | CREBBP | CREBBP | 6766 | 0.055 | 0.37 | NO
85 | MAPK9 | MAPK9 | MAPK9 | 6851 | 0.053 | 0.37 | NO
86 | PRKCB | PRKCB | PRKCB | 6914 | 0.052 | 0.37 | NO
87 | SIAH1 | SIAH1 | SIAH1 | 7075 | 0.048 | 0.36 | NO
88 | FZD5 | FZD5 | FZD5 | 7375 | 0.043 | 0.34 | NO
89 | VANGL1 | VANGL1 | VANGL1 | 7656 | 0.037 | 0.33 | NO
90 | ROCK2 | ROCK2 | ROCK2 | 7797 | 0.035 | 0.32 | NO
91 | RAC1 | RAC1 | RAC1 | 7907 | 0.032 | 0.32 | NO
92 | PPP2R1A | PPP2R1A | PPP2R1A | 7976 | 0.031 | 0.32 | NO
93 | DKK1 | DKK1 | DKK1 | 8103 | 0.029 | 0.31 | NO
94 | CSNK2A2 | CSNK2A2 | CSNK2A2 | 8173 | 0.028 | 0.31 | NO
95 | CTNNBIP1 | CTNNBIP1 | CTNNBIP1 | 8198 | 0.027 | 0.31 | NO
96 | CSNK2A1 | CSNK2A1 | CSNK2A1 | 8245 | 0.026 | 0.31 | NO
97 | AXIN1 | AXIN1 | AXIN1 | 8325 | 0.025 | 0.3 | NO
98 | CHP | CHP | CHP | 8901 | 0.014 | 0.27 | NO
99 | MAP3K7 | MAP3K7 | MAP3K7 | 9085 | 0.011 | 0.26 | NO
100 | ROCK1 | ROCK1 | ROCK1 | 9110 | 0.01 | 0.26 | NO
101 | PPP2CA | PPP2CA | PPP2CA | 9144 | 0.0098 | 0.26 | NO
102 | CAMK2D | CAMK2D | CAMK2D | 9173 | 0.0093 | 0.26 | NO
103 | RHOA | RHOA | RHOA | 9196 | 0.0089 | 0.26 | NO
104 | RAC3 | RAC3 | RAC3 | 9518 | 0.0027 | 0.24 | NO
105 | PSEN1 | PSEN1 | PSEN1 | 9832 | -0.0031 | 0.22 | NO
106 | WNT8B | WNT8B | WNT8B | 9877 | -0.004 | 0.22 | NO
107 | PPP3CC | PPP3CC | PPP3CC | 10241 | -0.011 | 0.2 | NO
108 | PRKACB | PRKACB | PRKACB | 10326 | -0.012 | 0.19 | NO
109 | CTBP1 | CTBP1 | CTBP1 | 10485 | -0.016 | 0.18 | NO
110 | SMAD4 | SMAD4 | SMAD4 | 10531 | -0.017 | 0.18 | NO
111 | FOSL1 | FOSL1 | FOSL1 | 10890 | -0.023 | 0.16 | NO
112 | NFATC3 | NFATC3 | NFATC3 | 10901 | -0.023 | 0.16 | NO
113 | DVL1 | DVL1 | DVL1 | 11135 | -0.028 | 0.15 | NO
114 | PPP2R5A | PPP2R5A | PPP2R5A | 11211 | -0.029 | 0.15 | NO
115 | RUVBL1 | RUVBL1 | RUVBL1 | 11442 | -0.035 | 0.14 | NO
116 | PPP2CB | PPP2CB | PPP2CB | 11552 | -0.037 | 0.13 | NO
117 | WNT3A | WNT3A | WNT3A | 11609 | -0.038 | 0.13 | NO
118 | DVL2 | DVL2 | DVL2 | 12119 | -0.049 | 0.1 | NO
119 | WNT10A | WNT10A | WNT10A | 12752 | -0.064 | 0.072 | NO
120 | PPP2R5D | PPP2R5D | PPP2R5D | 12811 | -0.066 | 0.072 | NO
121 | CHP2 | CHP2 | CHP2 | 12953 | -0.069 | 0.067 | NO
122 | FZD2 | FZD2 | FZD2 | 12974 | -0.07 | 0.069 | NO
123 | RBX1 | RBX1 | RBX1 | 13122 | -0.074 | 0.064 | NO
124 | CSNK2B | CSNK2B | CSNK2B | 13428 | -0.083 | 0.05 | NO
125 | PORCN | PORCN | PORCN | 13483 | -0.084 | 0.051 | NO
126 | FZD4 | FZD4 | FZD4 | 13521 | -0.086 | 0.053 | NO
127 | PLCB3 | PLCB3 | PLCB3 | 13681 | -0.09 | 0.048 | NO
128 | SOX17 | SOX17 | SOX17 | 14435 | -0.12 | 0.01 | NO
129 | MMP7 | MMP7 | MMP7 | 14520 | -0.12 | 0.011 | NO
130 | WNT2B | WNT2B | WNT2B | 14533 | -0.12 | 0.015 | NO
131 | CACYBP | CACYBP | CACYBP | 15062 | -0.15 | -0.0081 | NO
132 | JUN | JUN | JUN | 15116 | -0.15 | -0.0044 | NO
133 | WNT9B | WNT9B | WNT9B | 15392 | -0.17 | -0.013 | NO
134 | CCND3 | CCND3 | CCND3 | 15519 | -0.17 | -0.012 | NO
135 | WNT7A | WNT7A | WNT7A | 15580 | -0.18 | -0.0074 | NO
136 | DKK2 | DKK2 | DKK2 | 15932 | -0.21 | -0.018 | NO
137 | PPP2R1B | PPP2R1B | PPP2R1B | 15943 | -0.21 | -0.0092 | NO
138 | CAMK2A | CAMK2A | CAMK2A | 15992 | -0.21 | -0.0024 | NO
139 | PPARD | PPARD | PPARD | 16062 | -0.22 | 0.0037 | NO
140 | PLCB2 | PLCB2 | PLCB2 | 16947 | -0.32 | -0.032 | NO
141 | SFRP2 | SFRP2 | SFRP2 | 17229 | -0.37 | -0.032 | NO
142 | RAC2 | RAC2 | RAC2 | 17321 | -0.39 | -0.019 | NO
143 | PRKCA | PRKCA | PRKCA | 17451 | -0.44 | -0.0071 | NO
144 | WNT5B | WNT5B | WNT5B | 17580 | -0.5 | 0.0078 | NO

Figure S31. Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: BIOCARTA WNT PATHWAY.

Figure S32. Get High-res Image For the top 5 core enriched genes in the pathway: BIOCARTA WNT PATHWAY, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: KEGG CYSTEINE AND METHIONINE METABOLISM

Table S17. Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank | GENE | SYMBOL | DESC | LIST.LOC | S2N | RES | CORE_ENRICHMENT
--- | --- | --- | --- | --- | --- | --- | ---
1 | CTNNA2 | CTNNA2 | CTNNA2 | 86 | 0.66 | 0.039 | YES
2 | CACNA2D2 | CACNA2D2 | CACNA2D2 | 116 | 0.64 | 0.079 | YES
3 | CACNG2 | CACNG2 | CACNG2 | 133 | 0.63 | 0.12 | YES
4 | CACNB2 | CACNB2 | CACNB2 | 188 | 0.58 | 0.16 | YES
5 | LEF1 | LEF1 | LEF1 | 218 | 0.57 | 0.19 | YES
6 | CACNA2D1 | CACNA2D1 | CACNA2D1 | 286 | 0.52 | 0.22 | YES
7 | RYR2 | RYR2 | RYR2 | 589 | 0.42 | 0.23 | YES
8 | ITGA8 | ITGA8 | ITGA8 | 604 | 0.42 | 0.26 | YES
9 | CACNA1S | CACNA1S | CACNA1S | 652 | 0.41 | 0.28 | YES
10 | ITGA9 | ITGA9 | ITGA9 | 777 | 0.38 | 0.3 | YES
11 | ITGB8 | ITGB8 | ITGB8 | 778 | 0.38 | 0.33 | YES
12 | CACNA1D | CACNA1D | CACNA1D | 877 | 0.37 | 0.34 | YES
13 | LAMA2 | LAMA2 | LAMA2 | 1058 | 0.34 | 0.36 | YES
14 | TCF7 | TCF7 | TCF7 | 1094 | 0.33 | 0.38 | YES
15 | CACNA1C | CACNA1C | CACNA1C | 1201 | 0.32 | 0.39 | YES
16 | DMD | DMD | DMD | 1619 | 0.27 | 0.39 | YES
17 | CACNG7 | CACNG7 | CACNG7 | 1748 | 0.26 | 0.4 | YES
18 | ITGA1 | ITGA1 | ITGA1 | 1787 | 0.25 | 0.41 | YES
19 | SGCD | SGCD | SGCD | 1895 | 0.24 | 0.42 | YES
20 | CACNB1 | CACNB1 | CACNB1 | 2119 | 0.23 | 0.42 | YES
21 | ITGA2 | ITGA2 | ITGA2 | 2126 | 0.23 | 0.44 | YES
22 | CDH2 | CDH2 | CDH2 | 2163 | 0.22 | 0.45 | YES
23 | ITGA7 | ITGA7 | ITGA7 | 2179 | 0.22 | 0.46 | YES
24 | CACNB3 | CACNB3 | CACNB3 | 2201 | 0.22 | 0.48 | YES
25 | ACTN1 | ACTN1 | ACTN1 | 2237 | 0.22 | 0.49 | YES
26 | PKP2 | PKP2 | PKP2 | 2786 | 0.18 | 0.47 | NO
27 | TCF7L2 | TCF7L2 | TCF7L2 | 3024 | 0.17 | 0.47 | NO
28 | ITGB5 | ITGB5 | ITGB5 | 3057 | 0.17 | 0.48 | NO
29 | CTNNB1 | CTNNB1 | CTNNB1 | 3473 | 0.15 | 0.46 | NO
30 | CACNB4 | CACNB4 | CACNB4 | 4065 | 0.13 | 0.44 | NO
31 | TCF7L1 | TCF7L1 | TCF7L1 | 4210 | 0.12 | 0.44 | NO
32 | SGCB | SGCB | SGCB | 4274 | 0.12 | 0.44 | NO
33 | SGCA | SGCA | SGCA | 4925 | 0.099 | 0.41 | NO
34 | ITGA11 | ITGA11 | ITGA11 | 5080 | 0.095 | 0.41 | NO
35 | ITGA10 | ITGA10 | ITGA10 | 5304 | 0.089 | 0.4 | NO
36 | SGCG | SGCG | SGCG | 6571 | 0.059 | 0.33 | NO
37 | ITGA2B | ITGA2B | ITGA2B | 7205 | 0.046 | 0.3 | NO
38 | ITGB1 | ITGB1 | ITGB1 | 7295 | 0.044 | 0.3 | NO
39 | DES | DES | DES | 7682 | 0.037 | 0.28 | NO
40 | ITGA6 | ITGA6 | ITGA6 | 9037 | 0.012 | 0.2 | NO
41 | EMD | EMD | EMD | 9105 | 0.011 | 0.2 | NO
42 | CTNNA1 | CTNNA1 | CTNNA1 | 9577 | 0.0017 | 0.17 | NO
43 | ACTN3 | ACTN3 | ACTN3 | 9812 | -0.0026 | 0.16 | NO
44 | CACNG4 | CACNG4 | CACNG4 | 10121 | -0.0086 | 0.14 | NO
45 | ACTN2 | ACTN2 | ACTN2 | 10857 | -0.023 | 0.1 | NO
46 | DAG1 | DAG1 | DAG1 | 10977 | -0.025 | 0.098 | NO
47 | JUP | JUP | JUP | 11558 | -0.037 | 0.068 | NO
48 | ACTN4 | ACTN4 | ACTN4 | 12412 | -0.056 | 0.023 | NO
49 | ITGAV | ITGAV | ITGAV | 12710 | -0.063 | 0.011 | NO
50 | ACTB | ACTB | ACTB | 12718 | -0.063 | 0.014 | NO
51 | ACTG1 | ACTG1 | ACTG1 | 12796 | -0.065 | 0.014 | NO
52 | CTNNA3 | CTNNA3 | CTNNA3 | 13198 | -0.076 | -0.0035 | NO
53 | DSP | DSP | DSP | 13284 | -0.078 | -0.0032 | NO
54 | LMNA | LMNA | LMNA | 13782 | -0.093 | -0.025 | NO
55 | ATP2A2 | ATP2A2 | ATP2A2 | 14250 | -0.11 | -0.044 | NO
56 | DSG2 | DSG2 | DSG2 | 14332 | -0.11 | -0.042 | NO
57 | ITGA3 | ITGA3 | ITGA3 | 14530 | -0.12 | -0.045 | NO
58 | ITGB7 | ITGB7 | ITGB7 | 14814 | -0.13 | -0.052 | NO
59 | ITGB3 | ITGB3 | ITGB3 | 15039 | -0.14 | -0.056 | NO
60 | CACNA2D3 | CACNA2D3 | CACNA2D3 | 15071 | -0.15 | -0.048 | NO
61 | CACNA1F | CACNA1F | CACNA1F | 15302 | -0.16 | -0.05 | NO
62 | ITGA5 | ITGA5 | ITGA5 | 16012 | -0.22 | -0.076 | NO
63 | CACNG1 | CACNG1 | CACNG1 | 16184 | -0.24 | -0.07 | NO
64 | GJA1 | GJA1 | GJA1 | 16378 | -0.25 | -0.065 | NO
65 | ITGB4 | ITGB4 | ITGB4 | 16511 | -0.27 | -0.055 | NO
66 | ITGA4 | ITGA4 | ITGA4 | 16548 | -0.27 | -0.039 | NO
67 | SLC8A1 | SLC8A1 | SLC8A1 | 16920 | -0.32 | -0.039 | NO
68 | DSC2 | DSC2 | DSC2 | 17068 | -0.34 | -0.025 | NO
69 | CACNA2D4 | CACNA2D4 | CACNA2D4 | 17327 | -0.39 | -0.014 | NO
70 | ITGB6 | ITGB6 | ITGB6 | 17634 | -0.55 | 0.0047 | NO

Figure S33. Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: KEGG CYSTEINE AND METHIONINE METABOLISM.

Figure S34. Get High-res Image For the top 5 core enriched genes in the pathway: KEGG CYSTEINE AND METHIONINE METABOLISM, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: KEGG GLYCOSAMINOGLYCAN BIOSYNTHESIS HEPARAN SULFATE

Table S18. Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank | GENE | SYMBOL | DESC | LIST.LOC | S2N | RES | CORE_ENRICHMENT
--- | --- | --- | --- | --- | --- | --- | ---
1 | WNT4 | WNT4 | WNT4 | 108 | 0.65 | 0.056 | YES
2 | BMP6 | BMP6 | BMP6 | 230 | 0.56 | 0.1 | YES
3 | GLI1 | GLI1 | GLI1 | 368 | 0.49 | 0.14 | YES
4 | SHH | SHH | SHH | 487 | 0.46 | 0.18 | YES
5 | BMP4 | BMP4 | BMP4 | 556 | 0.43 | 0.22 | YES
6 | IHH | IHH | IHH | 591 | 0.42 | 0.25 | YES
7 | SMO | SMO | SMO | 656 | 0.41 | 0.29 | YES
8 | CSNK1A1L | CSNK1A1L | CSNK1A1L | 750 | 0.39 | 0.32 | YES
9 | BMP7 | BMP7 | BMP7 | 1029 | 0.34 | 0.34 | YES
10 | WNT9A | WNT9A | WNT9A | 1076 | 0.34 | 0.37 | YES
11 | WNT10B | WNT10B | WNT10B | 1336 | 0.3 | 0.38 | YES
12 | PTCH2 | PTCH2 | PTCH2 | 1585 | 0.28 | 0.39 | YES
13 | GLI3 | GLI3 | GLI3 | 1651 | 0.27 | 0.42 | YES
14 | HHIP | HHIP | HHIP | 2052 | 0.23 | 0.42 | YES
15 | PTCH1 | PTCH1 | PTCH1 | 2185 | 0.22 | 0.43 | YES
16 | WNT5A | WNT5A | WNT5A | 2446 | 0.2 | 0.43 | YES
17 | BMP8B | BMP8B | BMP8B | 2478 | 0.2 | 0.45 | YES
18 | PRKX | PRKX | PRKX | 2544 | 0.2 | 0.47 | YES
19 | ZIC2 | ZIC2 | ZIC2 | 2867 | 0.18 | 0.47 | YES
20 | WNT3 | WNT3 | WNT3 | 2981 | 0.17 | 0.48 | YES
21 | LRP2 | LRP2 | LRP2 | 3078 | 0.17 | 0.49 | YES
22 | WNT16 | WNT16 | WNT16 | 3241 | 0.16 | 0.49 | YES
23 | WNT2 | WNT2 | WNT2 | 3359 | 0.15 | 0.5 | YES
24 | BMP8A | BMP8A | BMP8A | 3592 | 0.14 | 0.5 | YES
25 | FBXW11 | FBXW11 | FBXW11 | 3752 | 0.14 | 0.5 | YES
26 | GLI2 | GLI2 | GLI2 | 4049 | 0.13 | 0.5 | NO
27 | CSNK1G3 | CSNK1G3 | CSNK1G3 | 4417 | 0.11 | 0.49 | NO
28 | BTRC | BTRC | BTRC | 4421 | 0.11 | 0.5 | NO
29 | WNT6 | WNT6 | WNT6 | 4856 | 0.1 | 0.49 | NO
30 | SUFU | SUFU | SUFU | 5171 | 0.092 | 0.48 | NO
31 | GSK3B | GSK3B | GSK3B | 5332 | 0.088 | 0.48 | NO
32 | PRKACG | PRKACG | PRKACG | 5438 | 0.085 | 0.48 | NO
33 | WNT11 | WNT11 | WNT11 | 5672 | 0.08 | 0.47 | NO
34 | CSNK1A1 | CSNK1A1 | CSNK1A1 | 5853 | 0.075 | 0.47 | NO
35 | WNT1 | WNT1 | WNT1 | 6283 | 0.066 | 0.45 | NO
36 | WNT7B | WNT7B | WNT7B | 6321 | 0.065 | 0.46 | NO
37 | PRKACA | PRKACA | PRKACA | 6667 | 0.057 | 0.44 | NO
38 | CSNK1E | CSNK1E | CSNK1E | 6707 | 0.056 | 0.44 | NO
39 | BMP2 | BMP2 | BMP2 | 6924 | 0.052 | 0.44 | NO
40 | GAS1 | GAS1 | GAS1 | 7380 | 0.043 | 0.42 | NO
41 | CSNK1G1 | CSNK1G1 | CSNK1G1 | 7846 | 0.034 | 0.39 | NO
42 | CSNK1G2 | CSNK1G2 | CSNK1G2 | 8304 | 0.025 | 0.37 | NO
43 | CSNK1D | CSNK1D | CSNK1D | 9591 | 0.0015 | 0.3 | NO
44 | WNT8B | WNT8B | WNT8B | 9877 | -0.004 | 0.28 | NO
45 | PRKACB | PRKACB | PRKACB | 10326 | -0.012 | 0.26 | NO
46 | WNT10A | WNT10A | WNT10A | 12752 | -0.064 | 0.13 | NO
47 | STK36 | STK36 | STK36 | 12829 | -0.066 | 0.13 | NO
48 | WNT2B | WNT2B | WNT2B | 14533 | -0.12 | 0.043 | NO
49 | RAB23 | RAB23 | RAB23 | 14845 | -0.14 | 0.039 | NO
50 | WNT9B | WNT9B | WNT9B | 15392 | -0.17 | 0.024 | NO
51 | WNT7A | WNT7A | WNT7A | 15580 | -0.18 | 0.03 | NO
52 | DHH | DHH | DHH | 17509 | -0.46 | -0.036 | NO
53 | WNT5B | WNT5B | WNT5B | 17580 | -0.5 | 0.0078 | NO

Figure S35. Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: KEGG GLYCOSAMINOGLYCAN BIOSYNTHESIS HEPARAN SULFATE.

Figure S36. Get High-res Image For the top 5 core enriched genes in the pathway: KEGG GLYCOSAMINOGLYCAN BIOSYNTHESIS HEPARAN SULFATE, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: KEGG MAPK SIGNALING PATHWAY

Table S19. Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank | GENE | SYMBOL | DESC | LIST.LOC | S2N | RES | CORE_ENRICHMENT
--- | --- | --- | --- | --- | --- | --- | ---
1 | NKD1 | NKD1 | NKD1 | 52 | 0.74 | 0.054 | YES
2 | WNT4 | WNT4 | WNT4 | 108 | 0.65 | 0.1 | YES
3 | WIF1 | WIF1 | WIF1 | 204 | 0.57 | 0.14 | YES
4 | LEF1 | LEF1 | LEF1 | 218 | 0.57 | 0.18 | YES
5 | PYGO1 | PYGO1 | PYGO1 | 277 | 0.53 | 0.22 | YES
6 | WISP1 | WISP1 | WISP1 | 540 | 0.44 | 0.24 | YES
7 | WNT9A | WNT9A | WNT9A | 1076 | 0.34 | 0.23 | YES
8 | TCF7 | TCF7 | TCF7 | 1094 | 0.33 | 0.26 | YES
9 | RHOU | RHOU | RHOU | 1286 | 0.31 | 0.27 | YES
10 | SFRP4 | SFRP4 | SFRP4 | 1322 | 0.3 | 0.29 | YES
11 | FZD7 | FZD7 | FZD7 | 1362 | 0.3 | 0.31 | YES
12 | FZD6 | FZD6 | FZD6 | 1551 | 0.28 | 0.32 | YES
13 | TLE1 | TLE1 | TLE1 | 2162 | 0.22 | 0.3 | YES
14 | LRP5 | LRP5 | LRP5 | 2209 | 0.22 | 0.32 | YES
15 | WNT5A | WNT5A | WNT5A | 2446 | 0.2 | 0.32 | YES
16 | CXXC4 | CXXC4 | CXXC4 | 2458 | 0.2 | 0.33 | YES
17 | FZD8 | FZD8 | FZD8 | 2592 | 0.2 | 0.34 | YES
18 | MYC | MYC | MYC | 2845 | 0.18 | 0.34 | YES
19 | WNT3 | WNT3 | WNT3 | 2981 | 0.17 | 0.35 | YES
20 | CTBP2 | CTBP2 | CTBP2 | 2998 | 0.17 | 0.36 | YES
21 | SFRP1 | SFRP1 | SFRP1 | 3163 | 0.16 | 0.36 | YES
22 | WNT16 | WNT16 | WNT16 | 3241 | 0.16 | 0.37 | YES
23 | FRZB | FRZB | FRZB | 3336 | 0.16 | 0.38 | YES
24 | WNT2 | WNT2 | WNT2 | 3359 | 0.15 | 0.39 | YES
25 | CTNNB1 | CTNNB1 | CTNNB1 | 3473 | 0.15 | 0.39 | YES
26 | CCND1 | CCND1 | CCND1 | 3579 | 0.14 | 0.4 | YES
27 | LRP6 | LRP6 | LRP6 | 3602 | 0.14 | 0.41 | YES
28 | FBXW11 | FBXW11 | FBXW11 | 3752 | 0.14 | 0.41 | YES
29 | DAAM1 | DAAM1 | DAAM1 | 4159 | 0.12 | 0.39 | YES
30 | FRAT1 | FRAT1 | FRAT1 | 4165 | 0.12 | 0.4 | YES
31 | TCF7L1 | TCF7L1 | TCF7L1 | 4210 | 0.12 | 0.41 | YES
32 | BTRC | BTRC | BTRC | 4421 | 0.11 | 0.41 | NO
33 | WNT6 | WNT6 | WNT6 | 4856 | 0.1 | 0.39 | NO
34 | APC | APC | APC | 5010 | 0.097 | 0.39 | NO
35 | GSK3B | GSK3B | GSK3B | 5332 | 0.088 | 0.38 | NO
36 | FZD3 | FZD3 | FZD3 | 5537 | 0.082 | 0.37 | NO
37 | WNT11 | WNT11 | WNT11 | 5672 | 0.08 | 0.37 | NO
38 | CCND2 | CCND2 | CCND2 | 5680 | 0.079 | 0.38 | NO
39 | FZD1 | FZD1 | FZD1 | 5728 | 0.078 | 0.38 | NO
40 | CSNK1A1 | CSNK1A1 | CSNK1A1 | 5853 | 0.075 | 0.38 | NO
41 | EP300 | EP300 | EP300 | 5989 | 0.072 | 0.38 | NO
42 | FBXW2 | FBXW2 | FBXW2 | 6214 | 0.068 | 0.37 | NO
43 | GSK3A | GSK3A | GSK3A | 6218 | 0.068 | 0.37 | NO
44 | WNT1 | WNT1 | WNT1 | 6283 | 0.066 | 0.37 | NO
45 | DIXDC1 | DIXDC1 | DIXDC1 | 6315 | 0.065 | 0.38 | NO
46 | WNT7B | WNT7B | WNT7B | 6321 | 0.065 | 0.38 | NO
47 | FBXW4 | FBXW4 | FBXW4 | 6344 | 0.064 | 0.39 | NO
48 | SENP2 | SENP2 | SENP2 | 6374 | 0.064 | 0.39 | NO
49 | NLK | NLK | NLK | 6569 | 0.059 | 0.38 | NO
50 | RPL13A | RPL13A | RPL13A | 6921 | 0.052 | 0.37 | NO
51 | FZD5 | FZD5 | FZD5 | 7375 | 0.043 | 0.34 | NO
52 | CSNK1G1 | CSNK1G1 | CSNK1G1 | 7846 | 0.034 | 0.32 | NO
53 | PPP2R1A | PPP2R1A | PPP2R1A | 7976 | 0.031 | 0.32 | NO
54 | DKK1 | DKK1 | DKK1 | 8103 | 0.029 | 0.31 | NO
55 | CTNNBIP1 | CTNNBIP1 | CTNNBIP1 | 8198 | 0.027 | 0.31 | NO
56 | CSNK2A1 | CSNK2A1 | CSNK2A1 | 8245 | 0.026 | 0.31 | NO
57 | AXIN1 | AXIN1 | AXIN1 | 8325 | 0.025 | 0.3 | NO
58 | HPRT1 | HPRT1 | HPRT1 | 8456 | 0.023 | 0.3 | NO
59 | PPP2CA | PPP2CA | PPP2CA | 9144 | 0.0098 | 0.26 | NO
60 | CSNK1D | CSNK1D | CSNK1D | 9591 | 0.0015 | 0.24 | NO
61 | GAPDH | GAPDH | GAPDH | 10234 | -0.011 | 0.2 | NO
62 | CTBP1 | CTBP1 | CTBP1 | 10485 | -0.016 | 0.19 | NO
63 | FOSL1 | FOSL1 | FOSL1 | 10890 | -0.023 | 0.16 | NO
64 | DVL1 | DVL1 | DVL1 | 11135 | -0.028 | 0.15 | NO
65 | DVL2 | DVL2 | DVL2 | 12119 | -0.049 | 0.1 | NO
66 | BCL9 | BCL9 | BCL9 | 12250 | -0.052 | 0.098 | NO
67 | ACTB | ACTB | ACTB | 12718 | -0.063 | 0.076 | NO
68 | WNT10A | WNT10A | WNT10A | 12752 | -0.064 | 0.079 | NO
69 | FZD2 | FZD2 | FZD2 | 12974 | -0.07 | 0.072 | NO
70 | AES | AES | AES | 13114 | -0.074 | 0.07 | NO
71 | PORCN | PORCN | PORCN | 13483 | -0.084 | 0.055 | NO
72 | FZD4 | FZD4 | FZD4 | 13521 | -0.086 | 0.06 | NO
73 | SOX17 | SOX17 | SOX17 | 14435 | -0.12 | 0.017 | NO
74 | TLE2 | TLE2 | TLE2 | 14460 | -0.12 | 0.024 | NO
75 | SLC9A3R1 | SLC9A3R1 | SLC9A3R1 | 14493 | -0.12 | 0.032 | NO
76 | WNT2B | WNT2B | WNT2B | 14533 | -0.12 | 0.039 | NO
77 | JUN | JUN | JUN | 15116 | -0.15 | 0.017 | NO
78 | CCND3 | CCND3 | CCND3 | 15519 | -0.17 | 0.0074 | NO
79 | B2M | B2M | B2M | 15543 | -0.18 | 0.02 | NO
80 | WNT7A | WNT7A | WNT7A | 15580 | -0.18 | 0.031 | NO
81 | KREMEN1 | KREMEN1 | KREMEN1 | 16232 | -0.24 | 0.012 | NO
82 | PITX2 | PITX2 | PITX2 | 17476 | -0.45 | -0.024 | NO
83 | WNT5B | WNT5B | WNT5B | 17580 | -0.5 | 0.0078 | NO

Figure S37. Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: KEGG MAPK SIGNALING PATHWAY.

Figure S38. Get High-res Image For the top 5 core enriched genes in the pathway: KEGG MAPK SIGNALING PATHWAY, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: KEGG WNT SIGNALING PATHWAY

Table S20. Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank | GENE | SYMBOL | DESC | LIST.LOC | S2N | RES | CORE_ENRICHMENT
--- | --- | --- | --- | --- | --- | --- | ---
1 | CDO1 | CDO1 | CDO1 | 156 | 0.61 | 0.17 | YES
2 | CBS | CBS | CBS | 546 | 0.44 | 0.27 | YES
3 | SMS | SMS | SMS | 1687 | 0.26 | 0.28 | YES
4 | TRDMT1 | TRDMT1 | TRDMT1 | 1722 | 0.26 | 0.36 | YES
5 | TAT | TAT | TAT | 1814 | 0.25 | 0.43 | YES
6 | BHMT | BHMT | BHMT | 4028 | 0.13 | 0.34 | NO
7 | MAT2B | MAT2B | MAT2B | 5604 | 0.081 | 0.27 | NO
8 | MPST | MPST | MPST | 5766 | 0.077 | 0.29 | NO
9 | LDHB | LDHB | LDHB | 6316 | 0.065 | 0.27 | NO
10 | AHCYL2 | AHCYL2 | AHCYL2 | 6516 | 0.06 | 0.28 | NO
11 | DNMT3A | DNMT3A | DNMT3A | 6653 | 0.058 | 0.29 | NO
12 | GOT1 | GOT1 | GOT1 | 6659 | 0.057 | 0.3 | NO
13 | CTH | CTH | CTH | 7673 | 0.037 | 0.26 | NO
14 | GOT2 | GOT2 | GOT2 | 8365 | 0.024 | 0.23 | NO
15 | DNMT1 | DNMT1 | DNMT1 | 8502 | 0.022 | 0.22 | NO
16 | LDHAL6B | LDHAL6B | LDHAL6B | 8591 | 0.02 | 0.23 | NO
17 | AHCY | AHCY | AHCY | 8746 | 0.017 | 0.22 | NO
18 | MTR | MTR | MTR | 8835 | 0.016 | 0.22 | NO
19 | MTAP | MTAP | MTAP | 9559 | 0.002 | 0.18 | NO
20 | MAT2A | MAT2A | MAT2A | 9771 | -0.0019 | 0.17 | NO
21 | AMD1 | AMD1 | AMD1 | 10253 | -0.011 | 0.15 | NO
22 | AHCYL1 | AHCYL1 | AHCYL1 | 10286 | -0.012 | 0.15 | NO
23 | ENOPH1 | ENOPH1 | ENOPH1 | 10332 | -0.013 | 0.15 | NO
24 | LDHAL6A | LDHAL6A | LDHAL6A | 10942 | -0.024 | 0.12 | NO
25 | APIP | APIP | APIP | 12767 | -0.064 | 0.037 | NO
26 | ADI1 | ADI1 | ADI1 | 12857 | -0.067 | 0.052 | NO
27 | SRM | SRM | SRM | 13000 | -0.07 | 0.064 | NO
28 | LDHA | LDHA | LDHA | 13583 | -0.087 | 0.057 | NO
29 | SDS | SDS | SDS | 14622 | -0.12 | 0.034 | NO
30 | MAT1A | MAT1A | MAT1A | 14695 | -0.13 | 0.067 | NO
31 | IL4I1 | IL4I1 | IL4I1 | 15388 | -0.17 | 0.076 | NO
32 | DNMT3B | DNMT3B | DNMT3B | 15734 | -0.19 | 0.11 | NO

Figure S39. Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: KEGG WNT SIGNALING PATHWAY.

Figure S40. Get High-res Image For the top 5 core enriched genes in the pathway: KEGG WNT SIGNALING PATHWAY, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

Fold change

For the top enriched genes, if you want to check whether they are

- up-regulated, please check the list of up-regulated genes

- down-regulated, please check the list of down-regulated genes

Expression level

For the top enriched genes, if you want to check whether they are

- highly expressed genes, please check the list of high (top 30%) expressed genes

- low expressed genes, please check the list of low (bottom 30%) expressed genes

An expression pattern of top(30%)/middle(30%)/low(30%) in this subtype against other subtypes is available in a heatmap

Significant gene list

For the top enriched genes, if you want to check whether they are

- significantly differently expressed genes by eBayes lm fit, please check the list of significant genes

Subtype clus3 enriched pathways

Table 5. Get Full Table This table shows top 10 pathways which are significantly enriched in cluster clus3. It displays only significant gene sets satisfying nom.p.val.threshold (-1), fwer.p.val.threshold (-1) , fdr.q.val.threshold (0.25) and the default table is sorted by Normalized Enrichment Score (NES). Further details on NES statistics, please visit The Broad GSEA website.

GeneSet(GS) | Size(#genes) | genes.ES.table | ES | NES | NOM.p.val | FDR.q.val | FWER.p.val | Tag.. | Gene.. | Signal | FDR..median. | glob.p.val
--- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | ---
BIOCARTA AT1R PATHWAY | 32 | genes.ES.table | 0.34 | 1.3 | 0.18 | 1 | 0.98 | 0.28 | 0.3 | 0.2 | 0.89 | 0.42
BIOCARTA EGF PATHWAY | 30 | genes.ES.table | 0.46 | 1.4 | 0.15 | 1 | 0.96 | 0.17 | 0.072 | 0.16 | 0.81 | 0.4
BIOCARTA GH PATHWAY | 26 | genes.ES.table | 0.43 | 1.4 | 0.083 | 1 | 0.95 | 0.15 | 0.054 | 0.15 | 1 | 0.52
BIOCARTA PYK2 PATHWAY | 27 | genes.ES.table | 0.32 | 1.3 | 0.22 | 0.82 | 0.99 | 0.22 | 0.3 | 0.16 | 0.71 | 0.3
BIOCARTA CHREBP2 PATHWAY | 41 | genes.ES.table | 0.34 | 1.2 | 0.24 | 0.79 | 0.99 | 0.32 | 0.27 | 0.23 | 0.69 | 0.27
BIOCARTA CREB PATHWAY | 26 | genes.ES.table | 0.51 | 1.6 | 0.021 | 0.88 | 0.76 | 0.23 | 0.16 | 0.19 | 0.57 | 0.31
KEGG PENTOSE PHOSPHATE PATHWAY | 25 | genes.ES.table | 0.42 | 1.3 | 0.17 | 0.87 | 0.99 | 0.48 | 0.34 | 0.32 | 0.75 | 0.34
KEGG STEROID HORMONE BIOSYNTHESIS | 41 | genes.ES.table | 0.56 | 1.4 | 0.062 | 1 | 0.95 | 0.51 | 0.15 | 0.44 | 0.9 | 0.44
KEGG O GLYCAN BIOSYNTHESIS | 27 | genes.ES.table | 0.45 | 1.3 | 0.12 | 0.78 | 0.99 | 0.41 | 0.2 | 0.33 | 0.67 | 0.28
KEGG BUTANOATE METABOLISM | 30 | genes.ES.table | 0.57 | 1.5 | 0.044 | 0.81 | 0.8 | 0.6 | 0.29 | 0.42 | 0.53 | 0.29

genes ES table in pathway: BIOCARTA AT1R PATHWAY

Table S21. Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank | GENE | SYMBOL | DESC | LIST.LOC | S2N | RES | CORE_ENRICHMENT
--- | --- | --- | --- | --- | --- | --- | ---
1 | RPA4 | RPA4 | RPA4 | 127 | 0.48 | 0.14 | YES
2 | ERCC4 | ERCC4 | ERCC4 | 1037 | 0.26 | 0.17 | YES
3 | ERCC8 | ERCC8 | ERCC8 | 2425 | 0.16 | 0.14 | YES
4 | GTF2H3 | GTF2H3 | GTF2H3 | 2734 | 0.14 | 0.17 | YES
5 | ERCC2 | ERCC2 | ERCC2 | 3079 | 0.13 | 0.19 | YES
6 | CDK7 | CDK7 | CDK7 | 3265 | 0.12 | 0.22 | YES
7 | GTF2H2 | GTF2H2 | GTF2H2 | 3407 | 0.12 | 0.24 | YES
8 | RPA3 | RPA3 | RPA3 | 3472 | 0.12 | 0.28 | YES
9 | LIG1 | LIG1 | LIG1 | 3639 | 0.11 | 0.3 | YES
10 | RPA2 | RPA2 | RPA2 | 3667 | 0.11 | 0.33 | YES
11 | POLE2 | POLE2 | POLE2 | 3781 | 0.11 | 0.36 | YES
12 | CUL4B | CUL4B | CUL4B | 4248 | 0.097 | 0.36 | YES
13 | CUL4A | CUL4A | CUL4A | 4256 | 0.096 | 0.39 | YES
14 | ERCC5 | ERCC5 | ERCC5 | 4634 | 0.088 | 0.4 | YES
15 | CCNH | CCNH | CCNH | 4792 | 0.084 | 0.42 | YES
16 | RFC2 | RFC2 | RFC2 | 5625 | 0.067 | 0.39 | NO
17 | GTF2H5 | GTF2H5 | GTF2H5 | 5629 | 0.067 | 0.41 | NO
18 | CETN2 | CETN2 | CETN2 | 6064 | 0.059 | 0.4 | NO
19 | MNAT1 | MNAT1 | MNAT1 | 6213 | 0.056 | 0.41 | NO
20 | RFC1 | RFC1 | RFC1 | 6663 | 0.048 | 0.4 | NO
21 | RFC3 | RFC3 | RFC3 | 6930 | 0.043 | 0.4 | NO
22 | POLD1 | POLD1 | POLD1 | 7285 | 0.037 | 0.39 | NO
23 | GTF2H4 | GTF2H4 | GTF2H4 | 7626 | 0.031 | 0.38 | NO
24 | RFC5 | RFC5 | RFC5 | 7665 | 0.031 | 0.39 | NO
25 | POLE4 | POLE4 | POLE4 | 7798 | 0.029 | 0.39 | NO
26 | POLE3 | POLE3 | POLE3 | 7905 | 0.027 | 0.39 | NO
27 | POLD2 | POLD2 | POLD2 | 8191 | 0.022 | 0.38 | NO
28 | POLE | POLE | POLE | 8248 | 0.021 | 0.39 | NO
29 | PCNA | PCNA | PCNA | 8729 | 0.013 | 0.36 | NO
30 | POLD3 | POLD3 | POLD3 | 8924 | 0.0096 | 0.36 | NO
31 | RAD23A | RAD23A | RAD23A | 9678 | -0.0028 | 0.32 | NO
32 | DDB1 | DDB1 | DDB1 | 9815 | -0.0048 | 0.31 | NO
33 | ERCC6 | ERCC6 | ERCC6 | 10019 | -0.0078 | 0.3 | NO
34 | GTF2H1 | GTF2H1 | GTF2H1 | 10262 | -0.012 | 0.29 | NO
35 | ERCC1 | ERCC1 | ERCC1 | 10697 | -0.019 | 0.27 | NO
36 | ERCC3 | ERCC3 | ERCC3 | 10741 | -0.02 | 0.28 | NO
37 | XPC | XPC | XPC | 11060 | -0.026 | 0.26 | NO
38 | RBX1 | RBX1 | RBX1 | 11852 | -0.039 | 0.23 | NO
39 | POLD4 | POLD4 | POLD4 | 12096 | -0.044 | 0.23 | NO
40 | RPA1 | RPA1 | RPA1 | 12994 | -0.064 | 0.2 | NO
41 | RFC4 | RFC4 | RFC4 | 13072 | -0.066 | 0.22 | NO
42 | XPA | XPA | XPA | 13357 | -0.073 | 0.22 | NO
43 | DDB2 | DDB2 | DDB2 | 13536 | -0.077 | 0.24 | NO

Figure S41. Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: BIOCARTA AT1R PATHWAY.

Figure S42. Get High-res Image For the top 5 core enriched genes in the pathway: BIOCARTA AT1R PATHWAY, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: BIOCARTA EGF PATHWAY

Table S22. Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank | GENE | SYMBOL | DESC | LIST.LOC | S2N | RES | CORE_ENRICHMENT
--- | --- | --- | --- | --- | --- | --- | ---
1 | SOCS1 | SOCS1 | SOCS1 | 163 | 0.46 | 0.04 | YES
2 | PARK2 | PARK2 | PARK2 | 533 | 0.34 | 0.055 | YES
3 | NHLRC1 | NHLRC1 | NHLRC1 | 576 | 0.33 | 0.088 | YES
4 | UBE2NL | UBE2NL | UBE2NL | 776 | 0.29 | 0.11 | YES
5 | HERC3 | HERC3 | HERC3 | 996 | 0.26 | 0.12 | YES
6 | UBE2QL1 | UBE2QL1 | UBE2QL1 | 1558 | 0.21 | 0.11 | YES
7 | ERCC8 | ERCC8 | ERCC8 | 2425 | 0.16 | 0.082 | YES
8 | UBE2D4 | UBE2D4 | UBE2D4 | 2654 | 0.15 | 0.084 | YES
9 | XIAP | XIAP | XIAP | 3298 | 0.12 | 0.061 | YES
10 | UBE2C | UBE2C | UBE2C | 3379 | 0.12 | 0.069 | YES
11 | CDC23 | CDC23 | CDC23 | 3499 | 0.12 | 0.074 | YES
12 | NEDD4 | NEDD4 | NEDD4 | 3550 | 0.11 | 0.084 | YES
13 | FBXO4 | FBXO4 | FBXO4 | 3644 | 0.11 | 0.09 | YES
14 | KLHL9 | KLHL9 | KLHL9 | 3882 | 0.11 | 0.088 | YES
15 | ANAPC10 | ANAPC10 | ANAPC10 | 3924 | 0.1 | 0.097 | YES
16 | UBE3C | UBE3C | UBE3C | 4026 | 0.1 | 0.1 | YES
17 | UBA6 | UBA6 | UBA6 | 4062 | 0.1 | 0.11 | YES
18 | UBE2A | UBE2A | UBE2A | 4198 | 0.098 | 0.11 | YES
19 | CUL4B | CUL4B | CUL4B | 4248 | 0.097 | 0.12 | YES
20 | CUL4A | CUL4A | CUL4A | 4256 | 0.096 | 0.13 | YES
21 | RCHY1 | RCHY1 | RCHY1 | 4286 | 0.096 | 0.14 | YES
22 | SAE1 | SAE1 | SAE1 | 4287 | 0.096 | 0.15 | YES
23 | UBE2B | UBE2B | UBE2B | 4357 | 0.094 | 0.16 | YES
24 | CDC20 | CDC20 | CDC20 | 4406 | 0.093 | 0.16 | YES
25 | NEDD4L | NEDD4L | NEDD4L | 4644 | 0.088 | 0.16 | YES
26 | UBE2K | UBE2K | UBE2K | 4683 | 0.087 | 0.17 | YES
27 | UBE2H | UBE2H | UBE2H | 4782 | 0.085 | 0.17 | YES
28 | MGRN1 | MGRN1 | MGRN1 | 4897 | 0.082 | 0.17 | YES
29 | UBE2D2 | UBE2D2 | UBE2D2 | 4958 | 0.08 | 0.18 | YES
30 | BIRC3 | BIRC3 | BIRC3 | 4968 | 0.08 | 0.18 | YES
31 | SKP1 | SKP1 | SKP1 | 5111 | 0.077 | 0.19 | YES
32 | RHOBTB2 | RHOBTB2 | RHOBTB2 | 5118 | 0.077 | 0.19 | YES
33 | UBE2D3 | UBE2D3 | UBE2D3 | 5150 | 0.076 | 0.2 | YES
34 | FZR1 | FZR1 | FZR1 | 5162 | 0.076 | 0.21 | YES
35 | SMURF1 | SMURF1 | SMURF1 | 5298 | 0.073 | 0.21 | YES
36 | ANAPC4 | ANAPC4 | ANAPC4 | 5385 | 0.072 | 0.21 | YES
37 | HUWE1 | HUWE1 | HUWE1 | 5476 | 0.07 | 0.21 | YES
38 | UBOX5 | UBOX5 | UBOX5 | 5547 | 0.068 | 0.22 | YES
39 | FBXW8 | FBXW8 | FBXW8 | 5658 | 0.066 | 0.22 | YES
40 | UBE2N | UBE2N | UBE2N | 5705 | 0.066 | 0.22 | YES
41 | FBXW11 | FBXW11 | FBXW11 | 5753 | 0.064 | 0.22 | YES
42 | UBE2I | UBE2I | UBE2I | 5802 | 0.064 | 0.23 | YES
43 | TCEB2 | TCEB2 | TCEB2 | 5881 | 0.062 | 0.23 | YES
44 | UBE3B | UBE3B | UBE3B | 5921 | 0.061 | 0.24 | YES
45 | UBA1 | UBA1 | UBA1 | 6011 | 0.06 | 0.24 | YES
46 | ANAPC5 | ANAPC5 | ANAPC5 | 6116 | 0.058 | 0.24 | YES
47 | UBE2S | UBE2S | UBE2S | 6128 | 0.058 | 0.24 | YES
48 | SIAH1 | SIAH1 | SIAH1 | 6175 | 0.057 | 0.25 | YES
49 | FANCL | FANCL | FANCL | 6189 | 0.056 | 0.25 | YES
50 | UBE2M | UBE2M | UBE2M | 6253 | 0.055 | 0.25 | YES
51 | UBE2E2 | UBE2E2 | UBE2E2 | 6364 | 0.053 | 0.25 | YES
52 | SKP2 | SKP2 | SKP2 | 6494 | 0.051 | 0.25 | YES
53 | UBE3A | UBE3A | UBE3A | 6580 | 0.05 | 0.25 | YES
54 | CUL1 | CUL1 | CUL1 | 6622 | 0.049 | 0.26 | YES
55 | PIAS4 | PIAS4 | PIAS4 | 6702 | 0.047 | 0.26 | YES
56 | SYVN1 | SYVN1 | SYVN1 | 7042 | 0.042 | 0.24 | NO
57 | CDC16 | CDC16 | CDC16 | 7071 | 0.041 | 0.24 | NO
58 | UBE2G2 | UBE2G2 | UBE2G2 | 7075 | 0.041 | 0.25 | NO
59 | HERC1 | HERC1 | HERC1 | 7286 | 0.037 | 0.24 | NO
60 | KEAP1 | KEAP1 | KEAP1 | 7425 | 0.035 | 0.24 | NO
61 | PPIL2 | PPIL2 | PPIL2 | 7587 | 0.032 | 0.23 | NO
62 | WWP2 | WWP2 | WWP2 | 7590 | 0.032 | 0.23 | NO
63 | ANAPC13 | ANAPC13 | ANAPC13 | 7751 | 0.03 | 0.23 | NO
64 | MAP3K1 | MAP3K1 | MAP3K1 | 7805 | 0.029 | 0.23 | NO
65 | ANAPC7 | ANAPC7 | ANAPC7 | 7837 | 0.028 | 0.23 | NO
66 | BIRC6 | BIRC6 | BIRC6 | 7943 | 0.026 | 0.22 | NO
67 | UBA2 | UBA2 | UBA2 | 7945 | 0.026 | 0.23 | NO
68 | MID1 | MID1 | MID1 | 8049 | 0.024 | 0.22 | NO
69 | UBE2R2 | UBE2R2 | UBE2R2 | 8186 | 0.022 | 0.22 | NO
70 | UBE4A | UBE4A | UBE4A | 8276 | 0.02 | 0.22 | NO
71 | FBXW7 | FBXW7 | FBXW7 | 8324 | 0.019 | 0.22 | NO
72 | HERC2 | HERC2 | HERC2 | 8387 | 0.018 | 0.21 | NO
73 | STUB1 | STUB1 | STUB1 | 8412 | 0.018 | 0.22 | NO
74 | CUL3 | CUL3 | CUL3 | 8537 | 0.016 | 0.21 | NO
75 | UBE2J1 | UBE2J1 | UBE2J1 | 8833 | 0.011 | 0.19 | NO
76 | TCEB1 | TCEB1 | TCEB1 | 8851 | 0.011 | 0.19 | NO
77 | ANAPC2 | ANAPC2 | ANAPC2 | 8923 | 0.0096 | 0.19 | NO
78 | CDC26 | CDC26 | CDC26 | 9091 | 0.0067 | 0.18 | NO
79 | CUL2 | CUL2 | CUL2 | 9226 | 0.0044 | 0.18 | NO
80 | CDC34 | CDC34 | CDC34 | 9451 | 0.00056 | 0.16 | NO
81 | BRCA1 | BRCA1 | BRCA1 | 9473 | 0.00023 | 0.16 | NO
82 | DDB1 | DDB1 | DDB1 | 9815 | -0.0048 | 0.14 | NO
83 | CUL7 | CUL7 | CUL7 | 9819 | -0.0048 | 0.14 | NO
84 | RNF7 | RNF7 | RNF7 | 9941 | -0.0067 | 0.14 | NO
85 | UBE2O | UBE2O | UBE2O | 10175 | -0.01 | 0.12 | NO
86 | UBE2W | UBE2W | UBE2W | 10185 | -0.011 | 0.12 | NO
87 | UBE2J2 | UBE2J2 | UBE2J2 | 10680 | -0.019 | 0.099 | NO
88 | ANAPC11 | ANAPC11 | ANAPC11 | 10756 | -0.02 | 0.097 | NO
89 | KLHL13 | KLHL13 | KLHL13 | 10779 | -0.021 | 0.098 | NO
90 | SOCS3 | SOCS3 | SOCS3 | 10890 | -0.022 | 0.094 | NO
91 | PIAS1 | PIAS1 | PIAS1 | 10909 | -0.023 | 0.096 | NO
92 | UBE2F | UBE2F | UBE2F | 11129 | -0.026 | 0.086 | NO
93 | TRIP12 | TRIP12 | TRIP12 | 11292 | -0.03 | 0.08 | NO
94 | PIAS2 | PIAS2 | PIAS2 | 11294 | -0.03 | 0.083 | NO
95 | CDC27 | CDC27 | CDC27 | 11322 | -0.03 | 0.085 | NO
96 | UBE2G1 | UBE2G1 | UBE2G1 | 11338 | -0.03 | 0.087 | NO
97 | DET1 | DET1 | DET1 | 11345 | -0.03 | 0.09 | NO
98 | CUL5 | CUL5 | CUL5 | 11395 | -0.031 | 0.09 | NO
99 | UBE2Z | UBE2Z | UBE2Z | 11465 | -0.032 | 0.09 | NO
100 | UBE2L3 | UBE2L3 | UBE2L3 | 11525 | -0.034 | 0.09 | NO
101 | UBE2Q2 | UBE2Q2 | UBE2Q2 | 11658 | -0.036 | 0.086 | NO
102 | ITCH | ITCH | ITCH | 11719 | -0.037 | 0.087 | NO
103 | UBA3 | UBA3 | UBA3 | 11794 | -0.038 | 0.087 | NO
104 | RBX1 | RBX1 | RBX1 | 11852 | -0.039 | 0.088 | NO
105 | PML | PML | PML | 11913 | -0.041 | 0.089 | NO
106 | UBR5 | UBR5 | UBR5 | 12246 | -0.047 | 0.075 | NO
107 | TRIM32 | TRIM32 | TRIM32 | 12374 | -0.05 | 0.073 | NO
108 | UBE2Q1 | UBE2Q1 | UBE2Q1 | 12398 | -0.051 | 0.077 | NO
109 | HERC4 | HERC4 | HERC4 | 12518 | -0.053 | 0.076 | NO
110 | CBL | CBL | CBL | 12732 | -0.058 | 0.07 | NO
111 | TRIM37 | TRIM37 | TRIM37 | 12839 | -0.06 | 0.071 | NO
112 | ANAPC1 | ANAPC1 | ANAPC1 | 12957 | -0.063 | 0.071 | NO
113 | UBE2L6 | UBE2L6 | UBE2L6 | 12990 | -0.064 | 0.076 | NO
114 | RFWD2 | RFWD2 | RFWD2 | 13053 | -0.065 | 0.079 | NO
115 | UBE2D1 | UBE2D1 | UBE2D1 | 13112 | -0.067 | 0.083 | NO
116 | TRAF6 | TRAF6 | TRAF6 | 13116 | -0.067 | 0.09 | NO
117 | UBE4B | UBE4B | UBE4B | 13314 | -0.072 | 0.086 | NO
118 | PIAS3 | PIAS3 | PIAS3 | 13332 | -0.072 | 0.093 | NO
119 | WWP1 | WWP1 | WWP1 | 13336 | -0.072 | 0.1 | NO
120 | DDB2 | DDB2 | DDB2 | 13536 | -0.077 | 0.098 | NO
121 | BIRC2 | BIRC2 | BIRC2 | 13606 | -0.079 | 0.1 | NO
122 | PRPF19 | PRPF19 | PRPF19 | 13807 | -0.084 | 0.1 | NO
123 | UBE2E3 | UBE2E3 | UBE2E3 | 13904 | -0.087 | 0.1 | NO
124 | AIRE | AIRE | AIRE | 14166 | -0.094 | 0.099 | NO
125 | UBE2E1 | UBE2E1 | UBE2E1 | 14372 | -0.1 | 0.098 | NO
126 | UBA7 | UBA7 | UBA7 | 14511 | -0.1 | 0.1 | NO
127 | VHL | VHL | VHL | 14675 | -0.11 | 0.1 | NO
128 | MDM2 | MDM2 | MDM2 | 14696 | -0.11 | 0.11 | NO
129 | CBLB | CBLB | CBLB | 14868 | -0.12 | 0.12 | NO
130 | FBXO2 | FBXO2 | FBXO2 | 16057 | -0.18 | 0.069 | NO
131 | SMURF2 | SMURF2 | SMURF2 | 16585 | -0.24 | 0.064 | NO

Figure S43. Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: BIOCARTA EGF PATHWAY.

Figure S44. Get High-res Image For the top 5 core enriched genes in the pathway: BIOCARTA EGF PATHWAY, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: BIOCARTA GH PATHWAY

Table S23. Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank | GENE | SYMBOL | DESC | LIST.LOC | S2N | RES | CORE_ENRICHMENT
--- | --- | --- | --- | --- | --- | --- | ---
1 | PRKCB | PRKCB | PRKCB | 111 | 0.5 | 0.2 | YES
2 | CAMK2B | CAMK2B | CAMK2B | 739 | 0.3 | 0.3 | YES
3 | PIK3R1 | PIK3R1 | PIK3R1 | 957 | 0.27 | 0.4 | YES
4 | PRKAR2B | PRKAR2B | PRKAR2B | 1360 | 0.23 | 0.47 | YES
5 | RPS6KA5 | RPS6KA5 | RPS6KA5 | 2646 | 0.15 | 0.46 | YES
6 | PRKCA | PRKCA | PRKCA | 2879 | 0.14 | 0.51 | YES
7 | PRKAR1B | PRKAR1B | PRKAR1B | 4760 | 0.085 | 0.44 | NO
8 | CAMK2D | CAMK2D | CAMK2D | 5264 | 0.074 | 0.44 | NO
9 | PRKACG | PRKACG | PRKACG | 5796 | 0.064 | 0.44 | NO
10 | PRKAR2A | PRKAR2A | PRKAR2A | 8427 | 0.018 | 0.29 | NO
11 | GNAS | GNAS | GNAS | 8593 | 0.015 | 0.29 | NO
12 | AKT1 | AKT1 | AKT1 | 8685 | 0.014 | 0.29 | NO
13 | PRKACB | PRKACB | PRKACB | 9213 | 0.0047 | 0.26 | NO
14 | RAC1 | RAC1 | RAC1 | 9464 | 0.00038 | 0.25 | NO
15 | SOS1 | SOS1 | SOS1 | 9786 | -0.0044 | 0.23 | NO
16 | MAPK14 | MAPK14 | MAPK14 | 9830 | -0.005 | 0.23 | NO
17 | MAPK3 | MAPK3 | MAPK3 | 9833 | -0.005 | 0.24 | NO
18 | GRB2 | GRB2 | GRB2 | 10200 | -0.011 | 0.22 | NO
19 | CAMK2G | CAMK2G | CAMK2G | 10576 | -0.017 | 0.21 | NO
20 | MAPK1 | MAPK1 | MAPK1 | 10708 | -0.019 | 0.21 | NO
21 | RPS6KA1 | RPS6KA1 | RPS6KA1 | 11996 | -0.042 | 0.15 | NO
22 | CREB1 | CREB1 | CREB1 | 12133 | -0.045 | 0.16 | NO
23 | PRKAR1A | PRKAR1A | PRKAR1A | 13265 | -0.071 | 0.13 | NO
24 | PIK3CA | PIK3CA | PIK3CA | 13737 | -0.083 | 0.14 | NO
25 | CAMK2A | CAMK2A | CAMK2A | 14364 | -0.1 | 0.14 | NO
26 | HRAS | HRAS | HRAS | 14538 | -0.11 | 0.18 | NO

Figure S45. Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: BIOCARTA GH PATHWAY.

Figure S46. Get High-res Image For the top 5 core enriched genes in the pathway: BIOCARTA GH PATHWAY, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: BIOCARTA PYK2 PATHWAY

Table S24. Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank | GENE | SYMBOL | DESC | LIST.LOC | S2N | RES | CORE_ENRICHMENT
--- | --- | --- | --- | --- | --- | --- | ---
1 | ACSM1 | ACSM1 | ACSM1 | 12 | 0.72 | 0.16 | YES
2 | ACSM3 | ACSM3 | ACSM3 | 55 | 0.57 | 0.28 | YES
3 | GAD1 | GAD1 | GAD1 | 283 | 0.41 | 0.36 | YES
4 | ABAT | ABAT | ABAT | 619 | 0.32 | 0.41 | YES
5 | ACSM5 | ACSM5 | ACSM5 | 894 | 0.28 | 0.45 | YES
6 | L2HGDH | L2HGDH | L2HGDH | 1134 | 0.25 | 0.49 | YES
7 | ACSM2A | ACSM2A | ACSM2A | 1657 | 0.2 | 0.51 | YES
8 | HMGCS1 | HMGCS1 | HMGCS1 | 1673 | 0.2 | 0.55 | YES
9 | ALDH5A1 | ALDH5A1 | ALDH5A1 | 2338 | 0.16 | 0.55 | YES
10 | AACS | AACS | AACS | 3292 | 0.12 | 0.52 | YES
11 | HMGCS2 | HMGCS2 | HMGCS2 | 3581 | 0.11 | 0.53 | YES
12 | HADH | HADH | HADH | 3720 | 0.11 | 0.54 | YES
13 | OXCT1 | OXCT1 | OXCT1 | 3756 | 0.11 | 0.56 | YES
14 | ALDH1B1 | ALDH1B1 | ALDH1B1 | 4497 | 0.091 | 0.54 | YES
15 | ACAT2 | ACAT2 | ACAT2 | 4531 | 0.09 | 0.56 | YES
16 | AKR1B10 | AKR1B10 | AKR1B10 | 5079 | 0.078 | 0.55 | YES
17 | ACADS | ACADS | ACADS | 5113 | 0.077 | 0.56 | YES
18 | PDHA1 | PDHA1 | PDHA1 | 5204 | 0.075 | 0.57 | YES
19 | ALDH3A2 | ALDH3A2 | ALDH3A2 | 5676 | 0.066 | 0.56 | NO
20 | BDH2 | BDH2 | BDH2 | 5776 | 0.064 | 0.57 | NO
21 | ALDH9A1 | ALDH9A1 | ALDH9A1 | 7111 | 0.04 | 0.5 | NO
22 | ECHS1 | ECHS1 | ECHS1 | 8106 | 0.024 | 0.45 | NO
23 | HMGCL | HMGCL | HMGCL | 8148 | 0.023 | 0.45 | NO
24 | ALDH7A1 | ALDH7A1 | ALDH7A1 | 8205 | 0.022 | 0.46 | NO
25 | ALDH2 | ALDH2 | ALDH2 | 8376 | 0.018 | 0.45 | NO
26 | OXCT2 | OXCT2 | OXCT2 | 9321 | 0.0028 | 0.4 | NO
27 | HADHA | HADHA | HADHA | 10980 | -0.024 | 0.31 | NO
28 | ACAT1 | ACAT1 | ACAT1 | 13376 | -0.073 | 0.19 | NO
29 | PDHB | PDHB | PDHB | 14552 | -0.11 | 0.15 | NO
30 | BDH1 | BDH1 | BDH1 | 15501 | -0.15 | 0.12 | NO

Figure S47. Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: BIOCARTA PYK2 PATHWAY.

Figure S48. Get High-res Image For the top 5 core enriched genes in the pathway: BIOCARTA PYK2 PATHWAY, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: BIOCARTA CHREBP2 PATHWAY

Table S25. Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank | GENE | SYMBOL | DESC | LIST.LOC | S2N | RES | CORE_ENRICHMENT
--- | --- | --- | --- | --- | --- | --- | ---
1 | MARS2 | MARS2 | MARS2 | 1805 | 0.19 | -0.013 | YES
2 | TARSL2 | TARSL2 | TARSL2 | 2707 | 0.14 | 0.0029 | YES
3 | RARS | RARS | RARS | 3921 | 0.1 | -0.017 | YES
4 | HARS2 | HARS2 | HARS2 | 4007 | 0.1 | 0.026 | YES
5 | HARS | HARS | HARS | 4010 | 0.1 | 0.074 | YES
6 | VARS2 | VARS2 | VARS2 | 4044 | 0.1 | 0.12 | YES
7 | PSTK | PSTK | PSTK | 4509 | 0.091 | 0.14 | YES
8 | MTFMT | MTFMT | MTFMT | 4589 | 0.089 | 0.17 | YES
9 | LARS | LARS | LARS | 4623 | 0.088 | 0.21 | YES
10 | GARS | GARS | GARS | 4945 | 0.081 | 0.23 | YES
11 | SEPSECS | SEPSECS | SEPSECS | 5015 | 0.079 | 0.26 | YES
12 | EARS2 | EARS2 | EARS2 | 5020 | 0.079 | 0.3 | YES
13 | YARS2 | YARS2 | YARS2 | 5667 | 0.066 | 0.3 | YES
14 | AARS2 | AARS2 | AARS2 | 5839 | 0.063 | 0.32 | YES
15 | SARS2 | SARS2 | SARS2 | 5854 | 0.063 | 0.34 | YES
16 | MARS | MARS | MARS | 5906 | 0.062 | 0.37 | YES
17 | FARS2 | FARS2 | FARS2 | 5933 | 0.061 | 0.4 | YES
18 | VARS | VARS | VARS | 6871 | 0.044 | 0.36 | NO
19 | FARSA | FARSA | FARSA | 7482 | 0.034 | 0.35 | NO
20 | KARS | KARS | KARS | 7637 | 0.031 | 0.35 | NO
21 | SARS | SARS | SARS | 7723 | 0.03 | 0.36 | NO
22 | LARS2 | LARS2 | LARS2 | 8460 | 0.017 | 0.33 | NO
23 | IARS2 | IARS2 | IARS2 | 8767 | 0.012 | 0.32 | NO
24 | IARS | IARS | IARS | 8768 | 0.012 | 0.32 | NO
25 | WARS | WARS | WARS | 8773 | 0.012 | 0.33 | NO
26 | FARSB | FARSB | FARSB | 8932 | 0.0095 | 0.32 | NO
27 | EPRS | EPRS | EPRS | 9028 | 0.0078 | 0.32 | NO
28 | NARS | NARS | NARS | 9050 | 0.0075 | 0.32 | NO
29 | PARS2 | PARS2 | PARS2 | 9070 | 0.0071 | 0.32 | NO
30 | TARS | TARS | TARS | 9122 | 0.0062 | 0.32 | NO
31 | NARS2 | NARS2 | NARS2 | 10337 | -0.013 | 0.26 | NO
32 | CARS2 | CARS2 | CARS2 | 10398 | -0.014 | 0.27 | NO
33 | DARS | DARS | DARS | 10614 | -0.018 | 0.26 | NO
34 | DARS2 | DARS2 | DARS2 | 11100 | -0.026 | 0.25 | NO
35 | YARS | YARS | YARS | 11330 | -0.03 | 0.25 | NO
36 | RARS2 | RARS2 | RARS2 | 11974 | -0.042 | 0.23 | NO
37 | AARS | AARS | AARS | 11990 | -0.042 | 0.25 | NO
38 | CARS | CARS | CARS | 12010 | -0.043 | 0.27 | NO
39 | WARS2 | WARS2 | WARS2 | 12108 | -0.044 | 0.28 | NO
40 | QARS | QARS | QARS | 13281 | -0.071 | 0.25 | NO

Figure S49. Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: BIOCARTA CHREBP2 PATHWAY.

Figure S50. Get High-res Image For the top 5 core enriched genes in the pathway: BIOCARTA CHREBP2 PATHWAY, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: BIOCARTA CREB PATHWAY

Table S26. Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank | GENE | SYMBOL | DESC | LIST.LOC | S2N | RES | CORE_ENRICHMENT
--- | --- | --- | --- | --- | --- | --- | ---
1 | PRKCB | PRKCB | PRKCB | 111 | 0.5 | 0.14 | YES
2 | SOCS1 | SOCS1 | SOCS1 | 163 | 0.46 | 0.28 | YES
3 | GHR | GHR | GHR | 352 | 0.38 | 0.38 | YES
4 | PIK3R1 | PIK3R1 | PIK3R1 | 957 | 0.27 | 0.43 | YES
5 | HNF1A | HNF1A | HNF1A | 2333 | 0.16 | 0.4 | NO
6 | PRKCA | PRKCA | PRKCA | 2879 | 0.14 | 0.41 | NO
7 | MAP2K1 | MAP2K1 | MAP2K1 | 4819 | 0.084 | 0.32 | NO
8 | INSR | INSR | INSR | 6005 | 0.06 | 0.28 | NO
9 | JAK2 | JAK2 | JAK2 | 8743 | 0.013 | 0.12 | NO
10 | SRF | SRF | SRF | 9318 | 0.0029 | 0.094 | NO
11 | SOS1 | SOS1 | SOS1 | 9786 | -0.0044 | 0.069 | NO
12 | MAPK3 | MAPK3 | MAPK3 | 9833 | -0.005 | 0.068 | NO
13 | GRB2 | GRB2 | GRB2 | 10200 | -0.011 | 0.05 | NO
14 | IRS1 | IRS1 | IRS1 | 10525 | -0.016 | 0.037 | NO
15 | MAPK1 | MAPK1 | MAPK1 | 10708 | -0.019 | 0.032 | NO
16 | STAT5B | STAT5B | STAT5B | 11160 | -0.027 | 0.015 | NO
17 | RAF1 | RAF1 | RAF1 | 11552 | -0.034 | 0.0032 | NO
18 | RPS6KA1 | RPS6KA1 | RPS6KA1 | 11996 | -0.042 | -0.0092 | NO
19 | SHC1 | SHC1 | SHC1 | 12134 | -0.045 | -0.0034 | NO
20 | STAT5A | STAT5A | STAT5A | 12798 | -0.059 | -0.023 | NO
21 | PTPN6 | PTPN6 | PTPN6 | 13285 | -0.071 | -0.029 | NO
22 | PLCG1 | PLCG1 | PLCG1 | 13290 | -0.071 | -0.0082 | NO
23 | PIK3CA | PIK3CA | PIK3CA | 13737 | -0.083 | -0.0086 | NO
24 | GH1 | GH1 | GH1 | 16502 | -0.22 | -0.098 | NO
25 | PIK3CG | PIK3CG | PIK3CG | 16917 | -0.28 | -0.039 | NO
26 | SLC2A4 | SLC2A4 | SLC2A4 | 16948 | -0.28 | 0.044 | NO

Figure S51. Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: BIOCARTA CREB PATHWAY.

Figure S52. Get High-res Image For the top 5 core enriched genes in the pathway: BIOCARTA CREB PATHWAY, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: KEGG PENTOSE PHOSPHATE PATHWAY

Table S27. Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank | GENE | SYMBOL | DESC | LIST.LOC | S2N | RES | CORE_ENRICHMENT
--- | --- | --- | --- | --- | --- | --- | ---
1 | CYP19A1 | CYP19A1 | CYP19A1 | 28 | 0.63 | 0.083 | YES
2 | CYP17A1 | CYP17A1 | CYP17A1 | 219 | 0.44 | 0.13 | YES
3 | AKR1D1 | AKR1D1 | AKR1D1 | 279 | 0.41 | 0.18 | YES
4 | CYP3A5 | CYP3A5 | CYP3A5 | 409 | 0.37 | 0.23 | YES
5 | CYP11A1 | CYP11A1 | CYP11A1 | 733 | 0.3 | 0.25 | YES
6 | STS | STS | STS | 943 | 0.27 | 0.27 | YES
7 | CYP3A43 | CYP3A43 | CYP3A43 | 1027 | 0.26 | 0.3 | YES
8 | SRD5A2 | SRD5A2 | SRD5A2 | 1221 | 0.24 | 0.32 | YES
9 | CYP3A7 | CYP3A7 | CYP3A7 | 1432 | 0.22 | 0.34 | YES
10 | SRD5A1 | SRD5A1 | SRD5A1 | 1595 | 0.2 | 0.36 | YES
11 | HSD17B6 | HSD17B6 | HSD17B6 | 1675 | 0.2 | 0.38 | YES
12 | AKR1C3 | AKR1C3 | AKR1C3 | 1691 | 0.2 | 0.41 | YES
13 | SULT1E1 | SULT1E1 | SULT1E1 | 1773 | 0.19 | 0.43 | YES
14 | AKR1C1 | AKR1C1 | AKR1C1 | 1923 | 0.18 | 0.45 | YES
15 | CYP7B1 | CYP7B1 | CYP7B1 | 1968 | 0.18 | 0.47 | YES
16 | CYP21A2 | CYP21A2 | CYP21A2 | 2022 | 0.18 | 0.49 | YES
17 | UGT2A1 | UGT2A1 | UGT2A1 | 2055 | 0.18 | 0.51 | YES
18 | CYP1A1 | CYP1A1 | CYP1A1 | 2123 | 0.17 | 0.53 | YES
19 | HSD17B3 | HSD17B3 | HSD17B3 | 2245 | 0.16 | 0.55 | YES
20 | UGT1A7 | UGT1A7 | UGT1A7 | 2574 | 0.15 | 0.55 | YES
21 | HSD3B2 | HSD3B2 | HSD3B2 | 2630 | 0.15 | 0.56 | YES
22 | HSD3B1 | HSD3B1 | HSD3B1 | 2970 | 0.13 | 0.56 | NO
23 | UGT2A3 | UGT2A3 | UGT2A3 | 3396 | 0.12 | 0.56 | NO
24 | CYP7A1 | CYP7A1 | CYP7A1 | 4493 | 0.091 | 0.5 | NO
25 | UGT1A6 | UGT1A6 | UGT1A6 | 5349 | 0.072 | 0.47 | NO
26 | AKR1C2 | AKR1C2 | AKR1C2 | 6556 | 0.05 | 0.4 | NO
27 | SRD5A3 | SRD5A3 | SRD5A3 | 7068 | 0.041 | 0.38 | NO
28 | HSD17B7 | HSD17B7 | HSD17B7 | 8296 | 0.02 | 0.32 | NO
29 | UGT2B4 | UGT2B4 | UGT2B4 | 8696 | 0.013 | 0.29 | NO
30 | CYP11B1 | CYP11B1 | CYP11B1 | 9734 | -0.0036 | 0.24 | NO
31 | COMT | COMT | COMT | 10863 | -0.022 | 0.18 | NO
32 | HSD17B8 | HSD17B8 | HSD17B8 | 13093 | -0.066 | 0.058 | NO
33 | CYP11B2 | CYP11B2 | CYP11B2 | 13519 | -0.077 | 0.044 | NO
34 | HSD17B12 | HSD17B12 | HSD17B12 | 14160 | -0.094 | 0.02 | NO
35 | CYP1B1 | CYP1B1 | CYP1B1 | 15350 | -0.14 | -0.028 | NO
36 | SULT2B1 | SULT2B1 | SULT2B1 | 15572 | -0.15 | -0.02 | NO
37 | HSD17B2 | HSD17B2 | HSD17B2 | 15610 | -0.16 | -0.00094 | NO
38 | HSD11B2 | HSD11B2 | HSD11B2 | 15641 | -0.16 | 0.018 | NO
39 | UGT1A9 | UGT1A9 | UGT1A9 | 16195 | -0.19 | 0.013 | NO
40 | HSD17B1 | HSD17B1 | HSD17B1 | 16858 | -0.27 | 0.012 | NO
41 | HSD11B1 | HSD11B1 | HSD11B1 | 16898 | -0.27 | 0.046 | NO

Figure S53. Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: KEGG PENTOSE PHOSPHATE PATHWAY.

Figure S54. Get High-res Image For the top 5 core enriched genes in the pathway: KEGG PENTOSE PHOSPHATE PATHWAY, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: KEGG STEROID HORMONE BIOSYNTHESIS

Table S28. Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank | GENE | SYMBOL | DESC | LIST.LOC | S2N | RES | CORE_ENRICHMENT
--- | --- | --- | --- | --- | --- | --- | ---
1 | POLR2J2 | POLR2J2 | POLR2J2 | 1346 | 0.23 | 0.048 | YES
2 | POLR3G | POLR3G | POLR3G | 1575 | 0.21 | 0.15 | YES
3 | POLR1E | POLR1E | POLR1E | 2798 | 0.14 | 0.16 | YES
4 | ZNRD1 | ZNRD1 | ZNRD1 | 2976 | 0.13 | 0.22 | YES
5 | POLR2J3 | POLR2J3 | POLR2J3 | 3204 | 0.12 | 0.28 | YES
6 | POLR3B | POLR3B | POLR3B | 3646 | 0.11 | 0.31 | YES
7 | POLR2B | POLR2B | POLR2B | 5090 | 0.078 | 0.27 | YES
8 | POLR2J | POLR2J | POLR2J | 5405 | 0.071 | 0.29 | YES
9 | POLR3K | POLR3K | POLR3K | 5503 | 0.069 | 0.33 | YES
10 | POLR2C | POLR2C | POLR2C | 5999 | 0.06 | 0.33 | YES
11 | POLR2F | POLR2F | POLR2F | 6160 | 0.057 | 0.35 | YES
12 | POLR2I | POLR2I | POLR2I | 6677 | 0.048 | 0.35 | NO
13 | POLR1C | POLR1C | POLR1C | 7939 | 0.026 | 0.29 | NO
14 | POLR3D | POLR3D | POLR3D | 8596 | 0.015 | 0.26 | NO
15 | POLR2E | POLR2E | POLR2E | 8895 | 0.01 | 0.25 | NO
16 | POLR1D | POLR1D | POLR1D | 9146 | 0.0058 | 0.24 | NO
17 | POLR2K | POLR2K | POLR2K | 9164 | 0.0056 | 0.24 | NO
18 | POLR2D | POLR2D | POLR2D | 9879 | -0.0058 | 0.21 | NO
19 | POLR2A | POLR2A | POLR2A | 9934 | -0.0066 | 0.21 | NO
20 | POLR3F | POLR3F | POLR3F | 10504 | -0.016 | 0.18 | NO
21 | POLR2L | POLR2L | POLR2L | 10520 | -0.016 | 0.19 | NO
22 | POLR3A | POLR3A | POLR3A | 11007 | -0.024 | 0.18 | NO
23 | POLR1B | POLR1B | POLR1B | 11946 | -0.041 | 0.15 | NO
24 | POLR1A | POLR1A | POLR1A | 11984 | -0.042 | 0.17 | NO
25 | POLR3GL | POLR3GL | POLR3GL | 12519 | -0.053 | 0.17 | NO
26 | POLR3H | POLR3H | POLR3H | 12943 | -0.063 | 0.18 | NO
27 | POLR2G | POLR2G | POLR2G | 13561 | -0.078 | 0.19 | NO
28 | POLR3C | POLR3C | POLR3C | 13940 | -0.088 | 0.21 | NO

Figure S55. Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: KEGG STEROID HORMONE BIOSYNTHESIS.

Figure S56. Get High-res Image For the top 5 core enriched genes in the pathway: KEGG STEROID HORMONE BIOSYNTHESIS, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: KEGG O GLYCAN BIOSYNTHESIS

Table S29. Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank | GENE | SYMBOL | DESC | LIST.LOC | S2N | RES | CORE_ENRICHMENT
--- | --- | --- | --- | --- | --- | --- | ---
1 | PRKCB | PRKCB | PRKCB | 111 | 0.5 | 0.14 | YES
2 | EGF | EGF | EGF | 156 | 0.46 | 0.27 | YES
3 | EGFR | EGFR | EGFR | 526 | 0.34 | 0.35 | YES
4 | PIK3R1 | PIK3R1 | PIK3R1 | 957 | 0.27 | 0.41 | YES
5 | RASA1 | RASA1 | RASA1 | 1280 | 0.23 | 0.46 | YES
6 | ELK1 | ELK1 | ELK1 | 2631 | 0.15 | 0.42 | NO
7 | PRKCA | PRKCA | PRKCA | 2879 | 0.14 | 0.45 | NO
8 | MAPK8 | MAPK8 | MAPK8 | 3572 | 0.11 | 0.44 | NO
9 | MAP2K1 | MAP2K1 | MAP2K1 | 4819 | 0.084 | 0.4 | NO
10 | STAT6 | STAT6 | STAT6 | 5495 | 0.07 | 0.38 | NO
11 | JAK1 | JAK1 | JAK1 | 7313 | 0.037 | 0.29 | NO
12 | MAP3K1 | MAP3K1 | MAP3K1 | 7805 | 0.029 | 0.27 | NO
13 | CSNK2A1 | CSNK2A1 | CSNK2A1 | 8436 | 0.018 | 0.24 | NO
14 | STAT3 | STAT3 | STAT3 | 8680 | 0.014 | 0.23 | NO
15 | JUN | JUN | JUN | 8887 | 0.01 | 0.22 | NO
16 | SRF | SRF | SRF | 9318 | 0.0029 | 0.2 | NO
17 | SOS1 | SOS1 | SOS1 | 9786 | -0.0044 | 0.17 | NO
18 | MAPK3 | MAPK3 | MAPK3 | 9833 | -0.005 | 0.17 | NO
19 | GRB2 | GRB2 | GRB2 | 10200 | -0.011 | 0.15 | NO
20 | MAP2K4 | MAP2K4 | MAP2K4 | 10579 | -0.017 | 0.14 | NO
21 | STAT5B | STAT5B | STAT5B | 11160 | -0.027 | 0.11 | NO
22 | RAF1 | RAF1 | RAF1 | 11552 | -0.034 | 0.1 | NO
23 | SHC1 | SHC1 | SHC1 | 12134 | -0.045 | 0.081 | NO
24 | STAT5A | STAT5A | STAT5A | 12798 | -0.059 | 0.061 | NO
25 | PLCG1 | PLCG1 | PLCG1 | 13290 | -0.071 | 0.054 | NO
26 | STAT2 | STAT2 | STAT2 | 13334 | -0.072 | 0.073 | NO
27 | PIK3CA | PIK3CA | PIK3CA | 13737 | -0.083 | 0.075 | NO
28 | STAT1 | STAT1 | STAT1 | 14123 | -0.093 | 0.08 | NO
29 | FOS | FOS | FOS | 14794 | -0.12 | 0.076 | NO
30 | STAT4 | STAT4 | STAT4 | 17116 | -0.3 | 0.034 | NO

Figure S57. Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: KEGG O GLYCAN BIOSYNTHESIS.

Figure S58. Get High-res Image For the top 5 core enriched genes in the pathway: KEGG O GLYCAN BIOSYNTHESIS, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: KEGG BUTANOATE METABOLISM

Table S30. Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank | GENE | SYMBOL | DESC | LIST.LOC | S2N | RES | CORE_ENRICHMENT
--- | --- | --- | --- | --- | --- | --- | ---
1 | CES7 | CES7 | CES7 | 2 | 0.89 | 0.16 | YES
2 | UPP2 | UPP2 | UPP2 | 317 | 0.4 | 0.21 | YES
3 | CYP3A5 | CYP3A5 | CYP3A5 | 409 | 0.37 | 0.27 | YES
4 | CYP2A6 | CYP2A6 | CYP2A6 | 567 | 0.33 | 0.32 | YES
5 | CYP3A43 | CYP3A43 | CYP3A43 | 1027 | 0.26 | 0.34 | YES
6 | CYP2A7 | CYP2A7 | CYP2A7 | 1063 | 0.26 | 0.39 | YES
7 | CYP3A7 | CYP3A7 | CYP3A7 | 1432 | 0.22 | 0.41 | YES
8 | XDH | XDH | XDH | 1503 | 0.21 | 0.44 | YES
9 | UGT2A1 | UGT2A1 | UGT2A1 | 2055 | 0.18 | 0.44 | YES
10 | DPYD | DPYD | DPYD | 2348 | 0.16 | 0.45 | YES
11 | HPRT1 | HPRT1 | HPRT1 | 2497 | 0.15 | 0.47 | YES
12 | UGT1A7 | UGT1A7 | UGT1A7 | 2574 | 0.15 | 0.5 | YES
13 | TPMT | TPMT | TPMT | 2717 | 0.14 | 0.51 | YES
14 | DPYS | DPYS | DPYS | 3240 | 0.12 | 0.5 | YES
15 | UGT2A3 | UGT2A3 | UGT2A3 | 3396 | 0.12 | 0.52 | YES
16 | NAT1 | NAT1 | NAT1 | 3771 | 0.11 | 0.52 | YES
17 | CES2 | CES2 | CES2 | 3939 | 0.1 | 0.52 | YES
18 | UPP1 | UPP1 | UPP1 | 4988 | 0.08 | 0.48 | NO
19 | UGT1A6 | UGT1A6 | UGT1A6 | 5349 | 0.072 | 0.47 | NO
20 | GUSB | GUSB | GUSB | 5577 | 0.068 | 0.47 | NO
21 | NAT2 | NAT2 | NAT2 | 8198 | 0.022 | 0.33 | NO
22 | CDA | CDA | CDA | 8317 | 0.02 | 0.32 | NO
23 | TK1 | TK1 | TK1 | 8347 | 0.019 | 0.33 | NO
24 | UGT2B4 | UGT2B4 | UGT2B4 | 8696 | 0.013 | 0.31 | NO
25 | ITPA | ITPA | ITPA | 8705 | 0.013 | 0.31 | NO
26 | TK2 | TK2 | TK2 | 8795 | 0.012 | 0.31 | NO
27 | CES1 | CES1 | CES1 | 9144 | 0.0058 | 0.29 | NO
28 | UCK1 | UCK1 | UCK1 | 10124 | -0.0096 | 0.24 | NO
29 | UPB1 | UPB1 | UPB1 | 10883 | -0.022 | 0.2 | NO
30 | UMPS | UMPS | UMPS | 11419 | -0.032 | 0.17 | NO
31 | UCKL1 | UCKL1 | UCKL1 | 12595 | -0.055 | 0.12 | NO
32 | IMPDH2 | IMPDH2 | IMPDH2 | 14616 | -0.11 | 0.021 | NO
33 | UCK2 | UCK2 | UCK2 | 14993 | -0.12 | 0.022 | NO
34 | GMPS | GMPS | GMPS | 15308 | -0.14 | 0.029 | NO
35 | IMPDH1 | IMPDH1 | IMPDH1 | 15843 | -0.17 | 0.029 | NO
36 | UGT1A9 | UGT1A9 | UGT1A9 | 16195 | -0.19 | 0.044 | NO
37 | TYMP | TYMP | TYMP | 16598 | -0.24 | 0.063 | NO

Figure S59. Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: KEGG BUTANOATE METABOLISM.

Figure S60. Get High-res Image For the top 5 core enriched genes in the pathway: KEGG BUTANOATE METABOLISM, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

Fold change

For the top enriched genes, if you want to check whether they are

- up-regulated, please check the list of up-regulated genes

- down-regulated, please check the list of down-regulated genes

Expression level

For the top enriched genes, if you want to check whether they are

- highly expressed genes, please check the list of high (top 30%) expressed genes

- low expressed genes, please check the list of low (bottom 30%) expressed genes

An expression pattern of top(30%)/middle(30%)/low(30%) in this subtype against other subtypes is available in a heatmap

Significant gene list

For the top enriched genes, if you want to check whether they are

- significantly differently expressed genes by eBayes lm fit, please check the list of significant genes

Subtype clus4 enriched pathways

Table 6. Get Full Table This table shows top 10 pathways which are significantly enriched in cluster clus4. It displays only significant gene sets satisfying nom.p.val.threshold (-1), fwer.p.val.threshold (-1) , fdr.q.val.threshold (0.25) and the default table is sorted by Normalized Enrichment Score (NES). Further details on NES statistics, please visit The Broad GSEA website.

GeneSet(GS) | Size(#genes) | genes.ES.table | ES | NES | NOM.p.val | FDR.q.val | FWER.p.val | Tag.. | Gene.. | Signal | FDR..median. | glob.p.val
--- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | ---
BIOCARTA BIOPEPTIDES PATHWAY | 38 | genes.ES.table | 0.45 | 1.5 | 0.056 | 0.2 | 0.87 | 0.24 | 0.19 | 0.19 | 0.15 | 0.004
BIOCARTA CARM ER PATHWAY | 34 | genes.ES.table | 0.41 | 1.5 | 0.054 | 0.21 | 0.85 | 0.12 | 0.07 | 0.11 | 0.15 | 0.011
BIOCARTA HDAC PATHWAY | 26 | genes.ES.table | 0.55 | 1.7 | 0.004 | 0.5 | 0.47 | 0.27 | 0.18 | 0.22 | 0 | 0.18
BIOCARTA EGF PATHWAY | 30 | genes.ES.table | 0.53 | 1.6 | 0.039 | 0.32 | 0.77 | 0.47 | 0.29 | 0.33 | 0.21 | 0.058
BIOCARTA FCER1 PATHWAY | 37 | genes.ES.table | 0.53 | 1.5 | 0.067 | 0.21 | 0.84 | 0.27 | 0.12 | 0.24 | 0.15 | 0.013
BIOCARTA GH PATHWAY | 26 | genes.ES.table | 0.47 | 1.5 | 0.04 | 0.2 | 0.86 | 0.19 | 0.094 | 0.18 | 0.15 | 0.005
BIOCARTA IL2RB PATHWAY | 37 | genes.ES.table | 0.72 | 1.9 | 0.002 | 0.18 | 0.089 | 0.35 | 0.097 | 0.32 | 0 | 0.072
BIOCARTA GSK3 PATHWAY | 26 | genes.ES.table | 0.51 | 1.6 | 0.021 | 0.36 | 0.73 | 0.19 | 0.12 | 0.17 | 0.23 | 0.08
BIOCARTA DEATH PATHWAY | 32 | genes.ES.table | 0.44 | 1.4 | 0.1 | 0.21 | 0.91 | 0.41 | 0.29 | 0.29 | 0.16 | 0.001
BIOCARTA KERATINOCYTE PATHWAY | 45 | genes.ES.table | 0.44 | 1.4 | 0.1 | 0.24 | 0.94 | 0.49 | 0.28 | 0.35 | 0.2 | 0.004

genes ES table in pathway: BIOCARTA BIOPEPTIDES PATHWAY

Table S31. Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank | GENE | SYMBOL | DESC | LIST.LOC | S2N | RES | CORE_ENRICHMENT
--- | --- | --- | --- | --- | --- | --- | ---
1 | IL2RB | IL2RB | IL2RB | 31 | 0.88 | 0.11 | YES
2 | FASLG | FASLG | FASLG | 138 | 0.68 | 0.19 | YES
3 | PIK3CG | PIK3CG | PIK3CG | 163 | 0.66 | 0.27 | YES
4 | IL2RG | IL2RG | IL2RG | 202 | 0.64 | 0.35 | YES
5 | IL2RA | IL2RA | IL2RA | 336 | 0.58 | 0.41 | YES
6 | IKZF3 | IKZF3 | IKZF3 | 395 | 0.55 | 0.48 | YES
7 | SYK | SYK | SYK | 545 | 0.5 | 0.53 | YES
8 | JAK3 | JAK3 | JAK3 | 794 | 0.44 | 0.58 | YES
9 | BCL2 | BCL2 | BCL2 | 1394 | 0.33 | 0.58 | YES
10 | PTPN6 | PTPN6 | PTPN6 | 1559 | 0.31 | 0.61 | YES
11 | STAT5A | STAT5A | STAT5A | 1627 | 0.3 | 0.65 | YES
12 | PIK3R1 | PIK3R1 | PIK3R1 | 1657 | 0.3 | 0.68 | YES
13 | FAS | FAS | FAS | 1721 | 0.29 | 0.72 | YES
14 | STAT5B | STAT5B | STAT5B | 2744 | 0.2 | 0.68 | NO
15 | MAPK3 | MAPK3 | MAPK3 | 4472 | 0.11 | 0.6 | NO
16 | JAK1 | JAK1 | JAK1 | 4779 | 0.097 | 0.6 | NO
17 | FOS | FOS | FOS | 6045 | 0.06 | 0.53 | NO
18 | CFLAR | CFLAR | CFLAR | 6344 | 0.052 | 0.52 | NO
19 | SOS1 | SOS1 | SOS1 | 6990 | 0.037 | 0.49 | NO
20 | BAD | BAD | BAD | 7089 | 0.034 | 0.49 | NO
21 | RPS6KB1 | RPS6KB1 | RPS6KB1 | 7186 | 0.032 | 0.49 | NO
22 | BCL2L1 | BCL2L1 | BCL2L1 | 7288 | 0.03 | 0.48 | NO
23 | SOCS3 | SOCS3 | SOCS3 | 7444 | 0.027 | 0.48 | NO
24 | GRB2 | GRB2 | GRB2 | 8173 | 0.012 | 0.44 | NO
25 | RAF1 | RAF1 | RAF1 | 8205 | 0.012 | 0.44 | NO
26 | PIK3CA | PIK3CA | PIK3CA | 8369 | 0.0084 | 0.43 | NO
27 | SHC1 | SHC1 | SHC1 | 8921 | -0.0026 | 0.4 | NO
28 | NMI | NMI | NMI | 8928 | -0.0029 | 0.4 | NO
29 | AKT1 | AKT1 | AKT1 | 9017 | -0.0045 | 0.4 | NO
30 | IRS1 | IRS1 | IRS1 | 10772 | -0.038 | 0.3 | NO
31 | CBL | CBL | CBL | 11295 | -0.049 | 0.28 | NO
32 | MAPK1 | MAPK1 | MAPK1 | 11645 | -0.056 | 0.26 | NO
33 | CRKL | CRKL | CRKL | 11706 | -0.058 | 0.27 | NO
34 | SOCS1 | SOCS1 | SOCS1 | 12933 | -0.088 | 0.21 | NO
35 | PPIA | PPIA | PPIA | 13454 | -0.1 | 0.19 | NO
36 | HRAS | HRAS | HRAS | 13470 | -0.1 | 0.21 | NO
37 | MYC | MYC | MYC | 16006 | -0.27 | 0.097 | NO

Figure S61. Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: BIOCARTA BIOPEPTIDES PATHWAY.

Figure S62. Get High-res Image For the top 5 core enriched genes in the pathway: BIOCARTA BIOPEPTIDES PATHWAY, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: BIOCARTA CARM ER PATHWAY

Table S32. Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank | GENE | SYMBOL | DESC | LIST.LOC | S2N | RES | CORE_ENRICHMENT
--- | --- | --- | --- | --- | --- | --- | ---
1 | UGT1A6 | UGT1A6 | UGT1A6 | 3 | 1 | 0.12 | YES
2 | UGT1A9 | UGT1A9 | UGT1A9 | 16 | 0.92 | 0.23 | YES
3 | UGT1A7 | UGT1A7 | UGT1A7 | 45 | 0.82 | 0.32 | YES
4 | AMY2A | AMY2A | AMY2A | 231 | 0.62 | 0.39 | YES
5 | AMY2B | AMY2B | AMY2B | 504 | 0.51 | 0.43 | YES
6 | ENPP1 | ENPP1 | ENPP1 | 526 | 0.51 | 0.49 | YES
7 | HK2 | HK2 | HK2 | 641 | 0.48 | 0.54 | YES
8 | UGT2A3 | UGT2A3 | UGT2A3 | 891 | 0.42 | 0.58 | YES
9 | AMY1A | AMY1A | AMY1A | 949 | 0.41 | 0.62 | YES
10 | UGT2A1 | UGT2A1 | UGT2A1 | 1083 | 0.38 | 0.66 | YES
11 | UGT2B4 | UGT2B4 | UGT2B4 | 2128 | 0.25 | 0.63 | NO
12 | GYS2 | GYS2 | GYS2 | 2244 | 0.24 | 0.65 | NO
13 | PYGB | PYGB | PYGB | 3516 | 0.15 | 0.6 | NO
14 | UGDH | UGDH | UGDH | 5625 | 0.071 | 0.49 | NO
15 | HK3 | HK3 | HK3 | 5732 | 0.068 | 0.49 | NO
16 | GAA | GAA | GAA | 6606 | 0.045 | 0.44 | NO
17 | PYGL | PYGL | PYGL | 6798 | 0.041 | 0.44 | NO
18 | AGL | AGL | AGL | 7755 | 0.02 | 0.39 | NO
19 | GANC | GANC | GANC | 7846 | 0.018 | 0.38 | NO
20 | UGP2 | UGP2 | UGP2 | 8066 | 0.014 | 0.37 | NO
21 | PGM1 | PGM1 | PGM1 | 8220 | 0.012 | 0.37 | NO
22 | GBE1 | GBE1 | GBE1 | 8642 | 0.0031 | 0.34 | NO
23 | GPI | GPI | GPI | 9033 | -0.0046 | 0.32 | NO
24 | GYS1 | GYS1 | GYS1 | 10842 | -0.04 | 0.22 | NO
25 | PGM2 | PGM2 | PGM2 | 11103 | -0.045 | 0.22 | NO
26 | MGAM | MGAM | MGAM | 12063 | -0.066 | 0.17 | NO
27 | HK1 | HK1 | HK1 | 13339 | -0.1 | 0.11 | NO
28 | PYGM | PYGM | PYGM | 13419 | -0.1 | 0.12 | NO
29 | GUSB | GUSB | GUSB | 13561 | -0.11 | 0.12 | NO
30 | G6PC2 | G6PC2 | G6PC2 | 14535 | -0.15 | 0.083 | NO
31 | GBA3 | GBA3 | GBA3 | 14730 | -0.16 | 0.091 | NO
32 | GCK | GCK | GCK | 15429 | -0.21 | 0.076 | NO
33 | PGM2L1 | PGM2L1 | PGM2L1 | 15507 | -0.22 | 0.097 | NO
34 | ENPP3 | ENPP3 | ENPP3 | 15716 | -0.24 | 0.11 | NO

Figure S63. Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: BIOCARTA CARM ER PATHWAY.

Figure S64. Get High-res Image For the top 5 core enriched genes in the pathway: BIOCARTA CARM ER PATHWAY, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: BIOCARTA HDAC PATHWAY

Table S33. Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank | GENE | SYMBOL | DESC | LIST.LOC | S2N | RES | CORE_ENRICHMENT
--- | --- | --- | --- | --- | --- | --- | ---
1 | IGF1 | IGF1 | IGF1 | 95 | 0.72 | 0.19 | YES
2 | PIK3CG | PIK3CG | PIK3CG | 163 | 0.66 | 0.36 | YES
3 | MAP2K6 | MAP2K6 | MAP2K6 | 1006 | 0.4 | 0.42 | YES
4 | PIK3R1 | PIK3R1 | PIK3R1 | 1657 | 0.3 | 0.47 | YES
5 | NFATC2 | NFATC2 | NFATC2 | 2108 | 0.25 | 0.51 | YES
6 | HDAC5 | HDAC5 | HDAC5 | 2984 | 0.18 | 0.51 | YES
7 | CAMK1G | CAMK1G | CAMK1G | 3168 | 0.17 | 0.55 | YES
8 | NFATC1 | NFATC1 | NFATC1 | 4772 | 0.097 | 0.48 | NO
9 | IGF1R | IGF1R | IGF1R | 6025 | 0.06 | 0.43 | NO
10 | PPP3CA | PPP3CA | PPP3CA | 6175 | 0.056 | 0.44 | NO
11 | PPP3CC | PPP3CC | PPP3CC | 7429 | 0.027 | 0.37 | NO
12 | MEF2A | MEF2A | MEF2A | 7868 | 0.018 | 0.35 | NO
13 | PIK3CA | PIK3CA | PIK3CA | 8369 | 0.0084 | 0.32 | NO
14 | MAPK7 | MAPK7 | MAPK7 | 8375 | 0.0082 | 0.33 | NO
15 | AKT1 | AKT1 | AKT1 | 9017 | -0.0045 | 0.29 | NO
16 | CABIN1 | CABIN1 | CABIN1 | 9655 | -0.016 | 0.26 | NO
17 | PPP3CB | PPP3CB | PPP3CB | 10164 | -0.026 | 0.24 | NO
18 | CALM1 | CALM1 | CALM1 | 10276 | -0.029 | 0.24 | NO
19 | MEF2D | MEF2D | MEF2D | 10534 | -0.034 | 0.24 | NO
20 | CAMK1 | CAMK1 | CAMK1 | 11781 | -0.06 | 0.18 | NO
21 | INSR | INSR | INSR | 12175 | -0.069 | 0.18 | NO
22 | YWHAH | YWHAH | YWHAH | 12597 | -0.079 | 0.18 | NO
23 | CALM3 | CALM3 | CALM3 | 12638 | -0.08 | 0.19 | NO
24 | CALM2 | CALM2 | CALM2 | 12956 | -0.089 | 0.2 | NO
25 | MAPK14 | MAPK14 | MAPK14 | 13897 | -0.12 | 0.18 | NO
26 | LOC729991-MEF2B | LOC729991-MEF2B | LOC729991-MEF2B | 14241 | -0.14 | 0.2 | NO

Figure S65. Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: BIOCARTA HDAC PATHWAY.

Figure S66. Get High-res Image For the top 5 core enriched genes in the pathway: BIOCARTA HDAC PATHWAY, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: BIOCARTA EGF PATHWAY

Table S34. Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank | GENE | SYMBOL | DESC | LIST.LOC | S2N | RES | CORE_ENRICHMENT
--- | --- | --- | --- | --- | --- | --- | ---
1 | STAT4 | STAT4 | STAT4 | 122 | 0.7 | 0.16 | YES
2 | PIK3CG | PIK3CG | PIK3CG | 163 | 0.66 | 0.31 | YES
3 | PRKCA | PRKCA | PRKCA | 301 | 0.59 | 0.44 | YES
4 | STAT5A | STAT5A | STAT5A | 1627 | 0.3 | 0.43 | YES
5 | PIK3R1 | PIK3R1 | PIK3R1 | 1657 | 0.3 | 0.5 | YES
6 | STAT5B | STAT5B | STAT5B | 2744 | 0.2 | 0.49 | YES
7 | STAT6 | STAT6 | STAT6 | 3336 | 0.16 | 0.49 | YES
8 | MAPK3 | MAPK3 | MAPK3 | 4472 | 0.11 | 0.45 | YES
9 | MAP3K1 | MAP3K1 | MAP3K1 | 4767 | 0.097 | 0.46 | YES
10 | MAP2K4 | MAP2K4 | MAP2K4 | 4774 | 0.097 | 0.48 | YES
11 | JAK1 | JAK1 | JAK1 | 4779 | 0.097 | 0.5 | YES
12 | JUN | JUN | JUN | 4911 | 0.093 | 0.52 | YES
13 | STAT2 | STAT2 | STAT2 | 4938 | 0.091 | 0.54 | YES
14 | STAT3 | STAT3 | STAT3 | 5143 | 0.085 | 0.55 | YES
15 | CSNK2A1 | CSNK2A1 | CSNK2A1 | 5932 | 0.062 | 0.52 | NO
16 | RASA1 | RASA1 | RASA1 | 5938 | 0.062 | 0.53 | NO
17 | FOS | FOS | FOS | 6045 | 0.06 | 0.54 | NO
18 | PRKCB | PRKCB | PRKCB | 6978 | 0.037 | 0.5 | NO
19 | SOS1 | SOS1 | SOS1 | 6990 | 0.037 | 0.5 | NO
20 | PDGFRA | PDGFRA | PDGFRA | 8054 | 0.014 | 0.45 | NO
21 | PLCG1 | PLCG1 | PLCG1 | 8085 | 0.014 | 0.45 | NO
22 | GRB2 | GRB2 | GRB2 | 8173 | 0.012 | 0.45 | NO
23 | RAF1 | RAF1 | RAF1 | 8205 | 0.012 | 0.45 | NO
24 | PIK3CA | PIK3CA | PIK3CA | 8369 | 0.0084 | 0.44 | NO
25 | SHC1 | SHC1 | SHC1 | 8921 | -0.0026 | 0.41 | NO
26 | SRF | SRF | SRF | 9251 | -0.0085 | 0.39 | NO
27 | STAT1 | STAT1 | STAT1 | 9907 | -0.022 | 0.36 | NO
28 | PDGFA | PDGFA | PDGFA | 11262 | -0.048 | 0.3 | NO
29 | MAP2K1 | MAP2K1 | MAP2K1 | 12405 | -0.074 | 0.25 | NO
30 | ELK1 | ELK1 | ELK1 | 12692 | -0.081 | 0.25 | NO
31 | MAPK8 | MAPK8 | MAPK8 | 14381 | -0.14 | 0.19 | NO

Figure S67. Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: BIOCARTA EGF PATHWAY.

Figure S68. Get High-res Image For the top 5 core enriched genes in the pathway: BIOCARTA EGF PATHWAY, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: BIOCARTA FCER1 PATHWAY

Table S35. Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank | GENE | SYMBOL | DESC | LIST.LOC | S2N | RES | CORE_ENRICHMENT
--- | --- | --- | --- | --- | --- | --- | ---
1 | ITK | ITK | ITK | 27 | 0.89 | 0.037 | YES
2 | CD247 | CD247 | CD247 | 62 | 0.78 | 0.07 | YES
3 | CD3E | CD3E | CD3E | 64 | 0.78 | 0.1 | YES
4 | PTPRC | PTPRC | PTPRC | 116 | 0.7 | 0.13 | YES
5 | CD40LG | CD40LG | CD40LG | 142 | 0.68 | 0.16 | YES
6 | GRAP2 | GRAP2 | GRAP2 | 158 | 0.67 | 0.19 | YES
7 | PIK3CG | PIK3CG | PIK3CG | 163 | 0.66 | 0.22 | YES
8 | CD28 | CD28 | CD28 | 183 | 0.65 | 0.24 | YES
9 | CD3G | CD3G | CD3G | 213 | 0.64 | 0.27 | YES
10 | CD8B | CD8B | CD8B | 242 | 0.62 | 0.3 | YES
11 | CD3D | CD3D | CD3D | 265 | 0.6 | 0.32 | YES
12 | CD8A | CD8A | CD8A | 279 | 0.6 | 0.35 | YES
13 | ICOS | ICOS | ICOS | 306 | 0.59 | 0.37 | YES
14 | ZAP70 | ZAP70 | ZAP70 | 308 | 0.59 | 0.4 | YES
15 | VAV3 | VAV3 | VAV3 | 322 | 0.58 | 0.42 | YES
16 | CD4 | CD4 | CD4 | 328 | 0.58 | 0.45 | YES
17 | LCK | LCK | LCK | 342 | 0.57 | 0.47 | YES
18 | LCP2 | LCP2 | LCP2 | 360 | 0.56 | 0.49 | YES
19 | PIK3CD | PIK3CD | PIK3CD | 513 | 0.51 | 0.51 | YES
20 | VAV1 | VAV1 | VAV1 | 889 | 0.42 | 0.5 | YES
21 | CTLA4 | CTLA4 | CTLA4 | 961 | 0.41 | 0.52 | YES
22 | PDCD1 | PDCD1 | PDCD1 | 1042 | 0.39 | 0.53 | YES
23 | TNF | TNF | TNF | 1337 | 0.34 | 0.53 | YES
24 | MAP3K8 | MAP3K8 | MAP3K8 | 1551 | 0.31 | 0.53 | YES
25 | PTPN6 | PTPN6 | PTPN6 | 1559 | 0.31 | 0.55 | YES
26 | LAT | LAT | LAT | 1652 | 0.3 | 0.55 | YES
27 | PIK3R1 | PIK3R1 | PIK3R1 | 1657 | 0.3 | 0.57 | YES
28 | RASGRP1 | RASGRP1 | RASGRP1 | 1814 | 0.28 | 0.57 | YES
29 | PIK3R5 | PIK3R5 | PIK3R5 | 1998 | 0.26 | 0.57 | YES
30 | CARD11 | CARD11 | CARD11 | 2060 | 0.25 | 0.58 | YES
31 | NFATC2 | NFATC2 | NFATC2 | 2108 | 0.25 | 0.59 | YES
32 | IL10 | IL10 | IL10 | 2438 | 0.22 | 0.58 | NO
33 | CSF2 | CSF2 | CSF2 | 2535 | 0.22 | 0.58 | NO
34 | IKBKB | IKBKB | IKBKB | 2693 | 0.21 | 0.58 | NO
35 | PAK7 | PAK7 | PAK7 | 2877 | 0.19 | 0.58 | NO
36 | AKT3 | AKT3 | AKT3 | 3103 | 0.18 | 0.57 | NO
37 | PIK3CB | PIK3CB | PIK3CB | 3429 | 0.16 | 0.56 | NO
38 | IFNG | IFNG | IFNG | 3532 | 0.15 | 0.56 | NO
39 | NFATC3 | NFATC3 | NFATC3 | 3724 | 0.14 | 0.56 | NO
40 | MAP3K14 | MAP3K14 | MAP3K14 | 3921 | 0.13 | 0.55 | NO
41 | FYN | FYN | FYN | 4175 | 0.12 | 0.55 | NO
42 | MAPK3 | MAPK3 | MAPK3 | 4472 | 0.11 | 0.53 | NO
43 | PIK3R2 | PIK3R2 | PIK3R2 | 4715 | 0.099 | 0.52 | NO
44 | NFATC1 | NFATC1 | NFATC1 | 4772 | 0.097 | 0.52 | NO
45 | NFKBIA | NFKBIA | NFKBIA | 4886 | 0.094 | 0.52 | NO
46 | JUN | JUN | JUN | 4911 | 0.093 | 0.52 | NO
47 | NFKB1 | NFKB1 | NFKB1 | 4945 | 0.091 | 0.53 | NO
48 | DLG1 | DLG1 | DLG1 | 4994 | 0.089 | 0.53 | NO
49 | NCK1 | NCK1 | NCK1 | 5107 | 0.086 | 0.52 | NO
50 | NFAT5 | NFAT5 | NFAT5 | 5187 | 0.084 | 0.52 | NO
51 | MAPK9 | MAPK9 | MAPK9 | 5210 | 0.083 | 0.53 | NO
52 | PAK3 | PAK3 | PAK3 | 5469 | 0.075 | 0.52 | NO
53 | MALT1 | MALT1 | MALT1 | 5924 | 0.062 | 0.49 | NO
54 | FOS | FOS | FOS | 6045 | 0.06 | 0.49 | NO
55 | PPP3CA | PPP3CA | PPP3CA | 6175 | 0.056 | 0.48 | NO
56 | NFKBIE | NFKBIE | NFKBIE | 6237 | 0.054 | 0.48 | NO
57 | PAK1 | PAK1 | PAK1 | 6317 | 0.053 | 0.48 | NO
58 | CDK4 | CDK4 | CDK4 | 6373 | 0.051 | 0.48 | NO
59 | NCK2 | NCK2 | NCK2 | 6388 | 0.051 | 0.48 | NO
60 | CBLB | CBLB | CBLB | 6956 | 0.038 | 0.45 | NO
61 | SOS1 | SOS1 | SOS1 | 6990 | 0.037 | 0.45 | NO
62 | PPP3CC | PPP3CC | PPP3CC | 7429 | 0.027 | 0.43 | NO
63 | IKBKG | IKBKG | IKBKG | 7452 | 0.026 | 0.43 | NO
64 | TEC | TEC | TEC | 7695 | 0.022 | 0.41 | NO
65 | PAK2 | PAK2 | PAK2 | 7769 | 0.02 | 0.41 | NO
66 | PLCG1 | PLCG1 | PLCG1 | 8085 | 0.014 | 0.39 | NO
67 | GRB2 | GRB2 | GRB2 | 8173 | 0.012 | 0.39 | NO
68 | PIK3R3 | PIK3R3 | PIK3R3 | 8181 | 0.012 | 0.39 | NO
69 | RAF1 | RAF1 | RAF1 | 8205 | 0.012 | 0.39 | NO
70 | PIK3CA | PIK3CA | PIK3CA | 8369 | 0.0084 | 0.38 | NO
71 | RELA | RELA | RELA | 8802 | -0.00044 | 0.35 | NO
72 | SOS2 | SOS2 | SOS2 | 8805 | -0.00059 | 0.35 | NO
73 | GSK3B | GSK3B | GSK3B | 9003 | -0.0042 | 0.34 | NO
74 | AKT1 | AKT1 | AKT1 | 9017 | -0.0045 | 0.34 | NO
75 | RHOA | RHOA | RHOA | 9240 | -0.0083 | 0.33 | NO
76 | CHP2 | CHP2 | CHP2 | 9457 | -0.013 | 0.32 | NO
77 | MAPK13 | MAPK13 | MAPK13 | 9640 | -0.016 | 0.31 | NO
78 | MAP3K7 | MAP3K7 | MAP3K7 | 9753 | -0.019 | 0.3 | NO
79 | MAP2K2 | MAP2K2 | MAP2K2 | 10117 | -0.026 | 0.28 | NO
80 | PPP3CB | PPP3CB | PPP3CB | 10164 | -0.026 | 0.28 | NO
81 | NFKBIB | NFKBIB | NFKBIB | 10189 | -0.027 | 0.28 | NO
82 | CDC42 | CDC42 | CDC42 | 10489 | -0.033 | 0.27 | NO
83 | BCL10 | BCL10 | BCL10 | 10492 | -0.033 | 0.27 | NO
84 | PRKCQ | PRKCQ | PRKCQ | 10545 | -0.034 | 0.27 | NO
85 | PPP3R1 | PPP3R1 | PPP3R1 | 10684 | -0.037 | 0.26 | NO
86 | MAP2K7 | MAP2K7 | MAP2K7 | 11117 | -0.045 | 0.24 | NO
87 | CBL | CBL | CBL | 11295 | -0.049 | 0.23 | NO
88 | MAPK1 | MAPK1 | MAPK1 | 11645 | -0.056 | 0.21 | NO
89 | CHUK | CHUK | CHUK | 12387 | -0.074 | 0.17 | NO
90 | MAP2K1 | MAP2K1 | MAP2K1 | 12405 | -0.074 | 0.18 | NO
91 | NRAS | NRAS | NRAS | 12488 | -0.076 | 0.18 | NO
92 | KRAS | KRAS | KRAS | 13044 | -0.091 | 0.15 | NO
93 | MAPK11 | MAPK11 | MAPK11 | 13383 | -0.1 | 0.13 | NO
94 | CHP | CHP | CHP | 13741 | -0.12 | 0.12 | NO
95 | MAPK14 | MAPK14 | MAPK14 | 13897 | -0.12 | 0.11 | NO
96 | AKT2 | AKT2 | AKT2 | 14564 | -0.15 | 0.083 | NO
97 | PAK4 | PAK4 | PAK4 | 14674 | -0.16 | 0.084 | NO
98 | PDK1 | PDK1 | PDK1 | 15910 | -0.26 | 0.025 | NO
99 | VAV2 | VAV2 | VAV2 | 16082 | -0.28 | 0.027 | NO
100 | MAPK12 | MAPK12 | MAPK12 | 16616 | -0.35 | 0.012 | NO
101 | PAK6 | PAK6 | PAK6 | 16712 | -0.37 | 0.023 | NO
102 | NFATC4 | NFATC4 | NFATC4 | 17665 | -0.77 | 0.003 | NO

Figure S69. Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: BIOCARTA FCER1 PATHWAY.

Figure S70. Get High-res Image For the top 5 core enriched genes in the pathway: BIOCARTA FCER1 PATHWAY, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: BIOCARTA GH PATHWAY

Table S36. Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank | GENE | SYMBOL | DESC | LIST.LOC | S2N | RES | CORE_ENRICHMENT
--- | --- | --- | --- | --- | --- | --- | ---
1 | HLA-DRB5 | HLA-DRB5 | HLA-DRB5 | 174 | 0.66 | 0.031 | YES
2 | HLA-DQA1 | HLA-DQA1 | HLA-DQA1 | 206 | 0.64 | 0.07 | YES
3 | HLA-DOA | HLA-DOA | HLA-DOA | 221 | 0.63 | 0.11 | YES
4 | CD8B | CD8B | CD8B | 242 | 0.62 | 0.15 | YES
5 | CD8A | CD8A | CD8A | 279 | 0.6 | 0.18 | YES
6 | HLA-DQA2 | HLA-DQA2 | HLA-DQA2 | 284 | 0.6 | 0.22 | YES
7 | KLRD1 | KLRD1 | KLRD1 | 303 | 0.59 | 0.25 | YES
8 | CD4 | CD4 | CD4 | 328 | 0.58 | 0.29 | YES
9 | HLA-DQB1 | HLA-DQB1 | HLA-DQB1 | 455 | 0.53 | 0.31 | YES
10 | CTSS | CTSS | CTSS | 562 | 0.5 | 0.34 | YES
11 | HLA-DRB1 | HLA-DRB1 | HLA-DRB1 | 584 | 0.49 | 0.37 | YES
12 | CIITA | CIITA | CIITA | 598 | 0.49 | 0.4 | YES
13 | HLA-DPA1 | HLA-DPA1 | HLA-DPA1 | 666 | 0.47 | 0.42 | YES
14 | IFI30 | IFI30 | IFI30 | 795 | 0.44 | 0.44 | YES
15 | HLA-DPB1 | HLA-DPB1 | HLA-DPB1 | 865 | 0.43 | 0.47 | YES
16 | LTA | LTA | LTA | 931 | 0.42 | 0.49 | YES
17 | HLA-DOB | HLA-DOB | HLA-DOB | 939 | 0.41 | 0.51 | YES
18 | KIR2DS4 | KIR2DS4 | KIR2DS4 | 1052 | 0.39 | 0.53 | YES
19 | HLA-DRA | HLA-DRA | HLA-DRA | 1065 | 0.39 | 0.56 | YES
20 | HLA-F | HLA-F | HLA-F | 1179 | 0.37 | 0.57 | YES
21 | CD74 | CD74 | CD74 | 1207 | 0.36 | 0.59 | YES
22 | KIR2DL1 | KIR2DL1 | KIR2DL1 | 1230 | 0.36 | 0.62 | YES
23 | HLA-DMA | HLA-DMA | HLA-DMA | 1492 | 0.32 | 0.62 | YES
24 | KIR3DL2 | KIR3DL2 | KIR3DL2 | 1493 | 0.32 | 0.64 | YES
25 | KIR3DL1 | KIR3DL1 | KIR3DL1 | 1778 | 0.28 | 0.64 | YES
26 | KLRC1 | KLRC1 | KLRC1 | 1887 | 0.27 | 0.65 | YES
27 | HLA-E | HLA-E | HLA-E | 2286 | 0.24 | 0.64 | YES
28 | HLA-B | HLA-B | HLA-B | 2307 | 0.24 | 0.66 | YES
29 | HLA-A | HLA-A | HLA-A | 2371 | 0.23 | 0.67 | YES
30 | KLRC4 | KLRC4 | KLRC4 | 2750 | 0.2 | 0.66 | YES
31 | KIR2DL3 | KIR2DL3 | KIR2DL3 | 2806 | 0.2 | 0.67 | YES
32 | HLA-C | HLA-C | HLA-C | 3011 | 0.18 | 0.67 | YES
33 | B2M | B2M | B2M | 3070 | 0.18 | 0.68 | YES
34 | HLA-DMB | HLA-DMB | HLA-DMB | 3348 | 0.16 | 0.67 | YES
35 | HLA-G | HLA-G | HLA-G | 3427 | 0.16 | 0.68 | YES
36 | NFYB | NFYB | NFYB | 3496 | 0.15 | 0.68 | YES
37 | CTSB | CTSB | CTSB | 3624 | 0.15 | 0.68 | YES
38 | KLRC3 | KLRC3 | KLRC3 | 3992 | 0.13 | 0.67 | NO
39 | HSPA2 | HSPA2 | HSPA2 | 4193 | 0.12 | 0.67 | NO
40 | TAPBP | TAPBP | TAPBP | 4406 | 0.11 | 0.66 | NO
41 | KIR2DL4 | KIR2DL4 | KIR2DL4 | 4593 | 0.1 | 0.66 | NO
42 | HSPA1L | HSPA1L | HSPA1L | 4771 | 0.097 | 0.66 | NO
43 | RFXAP | RFXAP | RFXAP | 5477 | 0.074 | 0.62 | NO
44 | TAP1 | TAP1 | TAP1 | 5513 | 0.073 | 0.62 | NO
45 | CTSL1 | CTSL1 | CTSL1 | 5530 | 0.073 | 0.63 | NO
46 | CANX | CANX | CANX | 5899 | 0.063 | 0.61 | NO
47 | CREB1 | CREB1 | CREB1 | 6212 | 0.055 | 0.6 | NO
48 | CALR | CALR | CALR | 6865 | 0.04 | 0.56 | NO
49 | HSP90AA1 | HSP90AA1 | HSP90AA1 | 7417 | 0.027 | 0.53 | NO
50 | LGMN | LGMN | LGMN | 7582 | 0.024 | 0.52 | NO
51 | PDIA3 | PDIA3 | PDIA3 | 7817 | 0.019 | 0.51 | NO
52 | PSME3 | PSME3 | PSME3 | 7960 | 0.016 | 0.5 | NO
53 | KLRC2 | KLRC2 | KLRC2 | 8097 | 0.014 | 0.5 | NO
54 | HSPA6 | HSPA6 | HSPA6 | 9274 | -0.0089 | 0.43 | NO
55 | HSPA4 | HSPA4 | HSPA4 | 9495 | -0.013 | 0.42 | NO
56 | HSPA1B | HSPA1B | HSPA1B | 9606 | -0.016 | 0.41 | NO
57 | NFYC | NFYC | NFYC | 9673 | -0.017 | 0.41 | NO
58 | TAP2 | TAP2 | TAP2 | 9733 | -0.018 | 0.41 | NO
59 | PSME1 | PSME1 | PSME1 | 10393 | -0.031 | 0.37 | NO
60 | HSPA5 | HSPA5 | HSPA5 | 11030 | -0.043 | 0.34 | NO
61 | HSPA8 | HSPA8 | HSPA8 | 11936 | -0.063 | 0.29 | NO
62 | HSPA1A | HSPA1A | HSPA1A | 12428 | -0.075 | 0.27 | NO
63 | NFYA | NFYA | NFYA | 12476 | -0.076 | 0.27 | NO
64 | RFX5 | RFX5 | RFX5 | 13276 | -0.098 | 0.23 | NO
65 | RFXANK | RFXANK | RFXANK | 13869 | -0.12 | 0.21 | NO
66 | PSME2 | PSME2 | PSME2 | 14962 | -0.17 | 0.16 | NO

Figure S71. Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: BIOCARTA GH PATHWAY.

Figure S72. Get High-res Image For the top 5 core enriched genes in the pathway: BIOCARTA GH PATHWAY, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: BIOCARTA IL2RB PATHWAY

Table S37. Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank | GENE | SYMBOL | DESC | LIST.LOC | S2N | RES | CORE_ENRICHMENT
--- | --- | --- | --- | --- | --- | --- | ---
1 | CCL5 | CCL5 | CCL5 | 119 | 0.7 | 0.09 | YES
2 | CASP1 | CASP1 | CASP1 | 152 | 0.67 | 0.18 | YES
3 | IL33 | IL33 | IL33 | 345 | 0.57 | 0.25 | YES
4 | PYCARD | PYCARD | PYCARD | 390 | 0.55 | 0.32 | YES
5 | IKBKE | IKBKE | IKBKE | 446 | 0.53 | 0.39 | YES
6 | RIPK3 | RIPK3 | RIPK3 | 797 | 0.44 | 0.43 | YES
7 | ZBP1 | ZBP1 | ZBP1 | 953 | 0.41 | 0.48 | YES
8 | CXCL10 | CXCL10 | CXCL10 | 989 | 0.4 | 0.54 | YES
9 | CCL4 | CCL4 | CCL4 | 1800 | 0.28 | 0.53 | YES
10 | IL18 | IL18 | IL18 | 1807 | 0.28 | 0.57 | YES
11 | TMEM173 | TMEM173 | TMEM173 | 2136 | 0.25 | 0.58 | YES
12 | IL1B | IL1B | IL1B | 2463 | 0.22 | 0.59 | YES
13 | CCL4L2 | CCL4L2 | CCL4L2 | 2532 | 0.22 | 0.62 | YES
14 | IRF7 | IRF7 | IRF7 | 2641 | 0.21 | 0.64 | YES
15 | IKBKB | IKBKB | IKBKB | 2693 | 0.21 | 0.67 | YES
16 | DDX58 | DDX58 | DDX58 | 4224 | 0.12 | 0.6 | NO
17 | AIM2 | AIM2 | AIM2 | 4852 | 0.094 | 0.58 | NO
18 | NFKBIA | NFKBIA | NFKBIA | 4886 | 0.094 | 0.59 | NO
19 | NFKB1 | NFKB1 | NFKB1 | 4945 | 0.091 | 0.6 | NO
20 | IL6 | IL6 | IL6 | 5982 | 0.061 | 0.55 | NO
21 | POLR3F | POLR3F | POLR3F | 6125 | 0.057 | 0.55 | NO
22 | POLR3GL | POLR3GL | POLR3GL | 6512 | 0.048 | 0.53 | NO
23 | POLR3G | POLR3G | POLR3G | 6687 | 0.044 | 0.53 | NO
24 | MAVS | MAVS | MAVS | 7031 | 0.036 | 0.51 | NO
25 | IKBKG | IKBKG | IKBKG | 7452 | 0.026 | 0.49 | NO
26 | RIPK1 | RIPK1 | RIPK1 | 7939 | 0.017 | 0.47 | NO
27 | POLR3B | POLR3B | POLR3B | 7952 | 0.016 | 0.47 | NO
28 | TBK1 | TBK1 | TBK1 | 7991 | 0.016 | 0.47 | NO
29 | IRF3 | IRF3 | IRF3 | 8027 | 0.015 | 0.47 | NO
30 | POLR3K | POLR3K | POLR3K | 8624 | 0.0035 | 0.44 | NO
31 | RELA | RELA | RELA | 8802 | -0.00044 | 0.43 | NO
32 | ADAR | ADAR | ADAR | 8997 | -0.0042 | 0.42 | NO
33 | TREX1 | TREX1 | TREX1 | 9786 | -0.019 | 0.37 | NO
34 | NFKBIB | NFKBIB | NFKBIB | 10189 | -0.027 | 0.35 | NO
35 | POLR3C | POLR3C | POLR3C | 11210 | -0.047 | 0.3 | NO
36 | POLR3D | POLR3D | POLR3D | 11802 | -0.06 | 0.28 | NO
37 | POLR1C | POLR1C | POLR1C | 12246 | -0.07 | 0.26 | NO
38 | CHUK | CHUK | CHUK | 12387 | -0.074 | 0.26 | NO
39 | POLR1D | POLR1D | POLR1D | 12900 | -0.087 | 0.25 | NO
40 | POLR3A | POLR3A | POLR3A | 12904 | -0.088 | 0.26 | NO
41 | POLR3H | POLR3H | POLR3H | 12940 | -0.089 | 0.27 | NO

Figure S73. Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: BIOCARTA IL2RB PATHWAY.

Figure S74. Get High-res Image For the top 5 core enriched genes in the pathway: BIOCARTA IL2RB PATHWAY, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: BIOCARTA GSK3 PATHWAY

Table S38. Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank | GENE | SYMBOL | DESC | LIST.LOC | S2N | RES | CORE_ENRICHMENT
--- | --- | --- | --- | --- | --- | --- | ---
1 | UGT1A6 | UGT1A6 | UGT1A6 | 3 | 1 | 0.18 | YES
2 | UGT1A9 | UGT1A9 | UGT1A9 | 16 | 0.92 | 0.33 | YES
3 | UGT1A7 | UGT1A7 | UGT1A7 | 45 | 0.82 | 0.47 | YES
4 | UGT2A3 | UGT2A3 | UGT2A3 | 891 | 0.42 | 0.5 | YES
5 | UGT2A1 | UGT2A1 | UGT2A1 | 1083 | 0.38 | 0.55 | YES
6 | UGT2B4 | UGT2B4 | UGT2B4 | 2128 | 0.25 | 0.53 | YES
7 | CP | CP | CP | 2251 | 0.24 | 0.57 | YES
8 | BLVRB | BLVRB | BLVRB | 2689 | 0.21 | 0.58 | YES
9 | ALAD | ALAD | ALAD | 3263 | 0.17 | 0.57 | YES
10 | FTH1 | FTH1 | FTH1 | 3863 | 0.13 | 0.56 | YES
11 | BLVRA | BLVRA | BLVRA | 4066 | 0.12 | 0.57 | YES
12 | COX10 | COX10 | COX10 | 4337 | 0.11 | 0.58 | YES
13 | UROD | UROD | UROD | 4395 | 0.11 | 0.59 | YES
14 | EARS2 | EARS2 | EARS2 | 5418 | 0.076 | 0.55 | NO
15 | FECH | FECH | FECH | 6913 | 0.039 | 0.47 | NO
16 | PPOX | PPOX | PPOX | 7242 | 0.031 | 0.46 | NO
17 | HMOX1 | HMOX1 | HMOX1 | 7512 | 0.025 | 0.45 | NO
18 | COX15 | COX15 | COX15 | 9007 | -0.0043 | 0.36 | NO
19 | ALAS2 | ALAS2 | ALAS2 | 9031 | -0.0046 | 0.36 | NO
20 | HMOX2 | HMOX2 | HMOX2 | 11067 | -0.044 | 0.25 | NO
21 | CPOX | CPOX | CPOX | 11586 | -0.055 | 0.23 | NO
22 | UROS | UROS | UROS | 12262 | -0.071 | 0.21 | NO
23 | MMAB | MMAB | MMAB | 13111 | -0.093 | 0.18 | NO
24 | ALAS1 | ALAS1 | ALAS1 | 13411 | -0.1 | 0.18 | NO
25 | GUSB | GUSB | GUSB | 13561 | -0.11 | 0.19 | NO
26 | HMBS | HMBS | HMBS | 14297 | -0.14 | 0.17 | NO
27 | EPRS | EPRS | EPRS | 14410 | -0.14 | 0.19 | NO

Figure S75. Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: BIOCARTA GSK3 PATHWAY.

Figure S76. Get High-res Image For the top 5 core enriched genes in the pathway: BIOCARTA GSK3 PATHWAY, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: BIOCARTA DEATH PATHWAY

Table S39. Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank | GENE | SYMBOL | DESC | LIST.LOC | S2N | RES | CORE_ENRICHMENT
--- | --- | --- | --- | --- | --- | --- | ---
1 | CD247 | CD247 | CD247 | 62 | 0.78 | 0.08 | YES
2 | CD3E | CD3E | CD3E | 64 | 0.78 | 0.16 | YES
3 | PIK3CG | PIK3CG | PIK3CG | 163 | 0.66 | 0.23 | YES
4 | CD3G | CD3G | CD3G | 213 | 0.64 | 0.29 | YES
5 | CD3D | CD3D | CD3D | 265 | 0.6 | 0.36 | YES
6 | PRKCA | PRKCA | PRKCA | 301 | 0.59 | 0.42 | YES
7 | ZAP70 | ZAP70 | ZAP70 | 308 | 0.59 | 0.48 | YES
8 | LCK | LCK | LCK | 342 | 0.57 | 0.54 | YES
9 | VAV1 | VAV1 | VAV1 | 889 | 0.42 | 0.55 | YES
10 | LAT | LAT | LAT | 1652 | 0.3 | 0.54 | YES
11 | PIK3R1 | PIK3R1 | PIK3R1 | 1657 | 0.3 | 0.57 | YES
12 | NFATC2 | NFATC2 | NFATC2 | 2108 | 0.25 | 0.58 | YES
13 | NFATC3 | NFATC3 | NFATC3 | 3724 | 0.14 | 0.5 | NO
14 | FYN | FYN | FYN | 4175 | 0.12 | 0.49 | NO
15 | MAPK3 | MAPK3 | MAPK3 | 4472 | 0.11 | 0.48 | NO
16 | MAP3K1 | MAP3K1 | MAP3K1 | 4767 | 0.097 | 0.48 | NO
17 | NFATC1 | NFATC1 | NFATC1 | 4772 | 0.097 | 0.49 | NO
18 | MAP2K4 | MAP2K4 | MAP2K4 | 4774 | 0.097 | 0.5 | NO
19 | NFKBIA | NFKBIA | NFKBIA | 4886 | 0.094 | 0.5 | NO
20 | JUN | JUN | JUN | 4911 | 0.093 | 0.51 | NO
21 | NFKB1 | NFKB1 | NFKB1 | 4945 | 0.091 | 0.52 | NO
22 | RASA1 | RASA1 | RASA1 | 5938 | 0.062 | 0.47 | NO
23 | FOS | FOS | FOS | 6045 | 0.06 | 0.47 | NO
24 | PPP3CA | PPP3CA | PPP3CA | 6175 | 0.056 | 0.47 | NO
25 | PRKCB | PRKCB | PRKCB | 6978 | 0.037 | 0.42 | NO
26 | SOS1 | SOS1 | SOS1 | 6990 | 0.037 | 0.43 | NO
27 | PPP3CC | PPP3CC | PPP3CC | 7429 | 0.027 | 0.41 | NO
28 | PLCG1 | PLCG1 | PLCG1 | 8085 | 0.014 | 0.37 | NO
29 | GRB2 | GRB2 | GRB2 | 8173 | 0.012 | 0.37 | NO
30 | RAF1 | RAF1 | RAF1 | 8205 | 0.012 | 0.37 | NO
31 | PIK3CA | PIK3CA | PIK3CA | 8369 | 0.0084 | 0.36 | NO
32 | RELA | RELA | RELA | 8802 | -0.00044 | 0.33 | NO
33 | SHC1 | SHC1 | SHC1 | 8921 | -0.0026 | 0.33 | NO
34 | RAC1 | RAC1 | RAC1 | 9616 | -0.016 | 0.29 | NO
35 | PPP3CB | PPP3CB | PPP3CB | 10164 | -0.026 | 0.26 | NO
36 | CALM1 | CALM1 | CALM1 | 10276 | -0.029 | 0.26 | NO
37 | MAP2K1 | MAP2K1 | MAP2K1 | 12405 | -0.074 | 0.15 | NO
38 | CALM3 | CALM3 | CALM3 | 12638 | -0.08 | 0.14 | NO
39 | ELK1 | ELK1 | ELK1 | 12692 | -0.081 | 0.15 | NO
40 | CALM2 | CALM2 | CALM2 | 12956 | -0.089 | 0.14 | NO
41 | MAPK8 | MAPK8 | MAPK8 | 14381 | -0.14 | 0.077 | NO
42 | PTPN7 | PTPN7 | PTPN7 | 15989 | -0.27 | 0.015 | NO
43 | NFATC4 | NFATC4 | NFATC4 | 17665 | -0.77 | 0.0029 | NO

Figure S77. Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: BIOCARTA DEATH PATHWAY.

Figure S78. Get High-res Image For the top 5 core enriched genes in the pathway: BIOCARTA DEATH PATHWAY, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

genes ES table in pathway: BIOCARTA KERATINOCYTE PATHWAY

Table S40. Get Full Table This table shows a Running Enrichment Score (RES) of each gene in this pathway, that is, the enrichment score at this point in the ranked list of genes. All genes are ranked by Signal-to-Noise (S2N), a measure of similarity as default and are used to obtain ES matrix of all genes. In this way, GSEA tool uses expression pattern of not only overlapped genes but also not-overlapped genes to produce ES matrix.

Rank | GENE | SYMBOL | DESC | LIST.LOC | S2N | RES | CORE_ENRICHMENT
--- | --- | --- | --- | --- | --- | --- | ---
1 | LY96 | LY96 | LY96 | 51 | 0.79 | 0.2 | YES
2 | CD14 | CD14 | CD14 | 252 | 0.61 | 0.34 | YES
3 | TLR4 | TLR4 | TLR4 | 561 | 0.5 | 0.45 | YES
4 | PIK3R1 | PIK3R1 | PIK3R1 | 1657 | 0.3 | 0.46 | YES
5 | GJA1 | GJA1 | GJA1 | 2031 | 0.26 | 0.51 | YES
6 | MYD88 | MYD88 | MYD88 | 4115 | 0.12 | 0.42 | NO
7 | NFKB1 | NFKB1 | NFKB1 | 4945 | 0.091 | 0.4 | NO
8 | FZD1 | FZD1 | FZD1 | 5451 | 0.075 | 0.39 | NO
9 | WNT1 | WNT1 | WNT1 | 5893 | 0.063 | 0.38 | NO
10 | DVL1 | DVL1 | DVL1 | 6502 | 0.048 | 0.36 | NO
11 | TIRAP | TIRAP | TIRAP | 6691 | 0.044 | 0.36 | NO
12 | APC | APC | APC | 6769 | 0.042 | 0.36 | NO
13 | PDPK1 | PDPK1 | PDPK1 | 7074 | 0.035 | 0.36 | NO
14 | GNAI1 | GNAI1 | GNAI1 | 7799 | 0.02 | 0.32 | NO
15 | PIK3CA | PIK3CA | PIK3CA | 8369 | 0.0084 | 0.29 | NO
16 | RELA | RELA | RELA | 8802 | -0.00044 | 0.27 | NO
17 | PPP2CA | PPP2CA | PPP2CA | 8919 | -0.0026 | 0.26 | NO
18 | GSK3B | GSK3B | GSK3B | 9003 | -0.0042 | 0.26 | NO
19 | AKT1 | AKT1 | AKT1 | 9017 | -0.0045 | 0.26 | NO
20 | LBP | LBP | LBP | 10154 | -0.026 | 0.2 | NO
21 | AXIN1 | AXIN1 | AXIN1 | 10940 | -0.041 | 0.17 | NO
22 | CCND1 | CCND1 | CCND1 | 12020 | -0.065 | 0.12 | NO
23 | IRAK1 | IRAK1 | IRAK1 | 12302 | -0.072 | 0.12 | NO
24 | EIF2AK2 | EIF2AK2 | EIF2AK2 | 13215 | -0.096 | 0.097 | NO
25 | CTNNB1 | CTNNB1 | CTNNB1 | 14224 | -0.14 | 0.074 | NO
26 | LEF1 | LEF1 | LEF1 | 17216 | -0.49 | 0.028 | NO

Figure S79. Get High-res Image This plot shows mRNAseq_cNMF expression data heatmap (on the left) a RunningEnrichmentScore(RES) plot (on the top right) and a Signal2Noise(S2N) plot (on the bottom right) of genes in the pathway: BIOCARTA KERATINOCYTE PATHWAY.

Figure S80. Get High-res Image For the top 5 core enriched genes in the pathway: BIOCARTA KERATINOCYTE PATHWAY, this volcano plot shows how much they are up/down-regulated and significant. The significance was calculated by empirical bayesian fit

Fold change

For the top enriched genes, if you want to check whether they are

- up-regulated, please check the list of up-regulated genes

- down-regulated, please check the list of down-regulated genes

Expression level

For the top enriched genes, if you want to check whether they are

- highly expressed genes, please check the list of high (top 30%) expressed genes

- low expressed genes, please check the list of low (bottom 30%) expressed genes

An expression pattern of top(30%)/middle(30%)/low(30%) in this subtype against other subtypes is available in a heatmap

Significant gene list

For the top enriched genes, if you want to check whether they are

- significantly differently expressed genes by eBayes lm fit, please check the list of significant genes

Methods & Data
Input

- Gene set database = c2.cp.v3.0-2.symbols.gmt

- Expression data file = ACC-TP.uncv2.mRNAseq_RSEM_normalized_log2.txt

- Phenotype data file = ACC-TP.mergedcluster.txt

GSEA analysis

For the Gene Set Enrichment Analysis (GSEA), Broad GSEA-P-R.1.0 version is used with class2: canonical pathways geneses from MSigDB. Further details about statistics are available inThe Broad GSEA website.

Download Results

In addition to the links below, the full results of the analysis summarized in this report can also be downloaded programmatically using firehose_get, or interactively from either the Broad GDAC website or TCGA Data Coordination Center Portal.

- Analysis Results (MD5 checksum)

- Auxiliary Data (MD5 checksum)

- MAGE-TAB File (MD5 checksum)

References
[1] Subramanian, A. et al, Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles., Proc. Natl. Acad. Sci. USA 102(43) (2005)
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